Hands On Artificial Intelligence for Beginners

Hands On Artificial Intelligence for Beginners
Author: Patrick D. Smith
Publsiher: Packt Publishing Ltd
Total Pages: 362
Release: 2018-10-31
ISBN: 1788992261
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence for Beginners Book Excerpt:

Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key Features Enter the world of AI with the help of solid concepts and real-world use cases Explore AI components to build real-world automated intelligence Become well versed with machine learning and deep learning concepts Book Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learn Use TensorFlow packages to create AI systems Build feedforward, convolutional, and recurrent neural networks Implement generative models for text generation Build reinforcement learning algorithms to play games Assemble RNNs, CNNs, and decoders to create an intelligent assistant Utilize RNNs to predict stock market behavior Create and scale training pipelines and deployment architectures for AI systems Who this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.

Hands On Artificial Intelligence with Java for Beginners

Hands On Artificial Intelligence with Java for Beginners
Author: Nisheeth Joshi
Publsiher: Packt Publishing Ltd
Total Pages: 144
Release: 2018-08-31
ISBN: 1789531020
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence with Java for Beginners Book Excerpt:

Build, train, and deploy intelligent applications using Java libraries Key Features Leverage the power of Java libraries to build smart applications Build and train deep learning models for implementing artificial intelligence Learn various algorithms to automate complex tasks Book Description Artificial intelligence (AI) is increasingly in demand as well as relevant in the modern world, where everything is driven by technology and data. AI can be used for automating systems or processes to carry out complex tasks and functions in order to achieve optimal performance and productivity. Hands-On Artificial Intelligence with Java for Beginners begins by introducing you to AI concepts and algorithms. You will learn about various Java-based libraries and frameworks that can be used in implementing AI to build smart applications. In addition to this, the book teaches you how to implement easy to complex AI tasks, such as genetic programming, heuristic searches, reinforcement learning, neural networks, and segmentation, all with a practical approach. By the end of this book, you will not only have a solid grasp of AI concepts, but you'll also be able to build your own smart applications for multiple domains. What you will learn Leverage different Java packages and tools such as Weka, RapidMiner, and Deeplearning4j, among others Build machine learning models using supervised and unsupervised machine learning techniques Implement different deep learning algorithms in Deeplearning4j and build applications based on them Study the basics of heuristic searching and genetic programming Differentiate between syntactic and semantic similarity among texts Perform sentiment analysis for effective decision making with LingPipe Who this book is for Hands-On Artificial Intelligence with Java for Beginners is for Java developers who want to learn the fundamentals of artificial intelligence and extend their programming knowledge to build smarter applications.

Artificial Intelligence For Dummies

Artificial Intelligence For Dummies
Author: John Paul Mueller,Luca Massaron
Publsiher: John Wiley & Sons
Total Pages: 336
Release: 2018-04-17
ISBN: 1119467659
Category: Computers
Language: EN, FR, DE, ES & NL

Artificial Intelligence For Dummies Book Excerpt:

Step into the future with AI The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!

Machine Learning in Python

Machine Learning in Python
Author: Bob Mather
Publsiher: Abiprod Pty Ltd
Total Pages: 83
Release: 2019-11-16
ISBN: 1922300039
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning in Python Book Excerpt:

Are you excited about Artificial Intelligence and want to get started?Are you excited about Machine Learning and want to learn how to implement in Python? The book below is the answer. Given the large amounts of data we use everyday; whether it is in the web, supermarkets, social media etc. analysis of data has become integral to our daily life. The ability to do so effectively can propel your career or business to great heights. Machine Learning is the most effective data analysis tool. While it is a complex topic, it can be broken down into simpler steps, as show in this book. We are using Python, which is a great programming language for beginners. Python is a great language that is commonly used with Machine Learning. Python is used extensively in Mathematics, Gaming and Graphic Design. It is fast to develop and prototype. It is web capable, meaning that we can use Python to gather web data. It is adaptable, and has great community of users. Here's What's Included In This Book: What is Machine Learning?Why use Python?Regression Analysis using Python with an exampleClustering Analysis using Python with an exampleImplementing an Artificial Neural NetworkBackpropagation90 Day Plan to Learn and Implement Machine LearningConclusion

Hands On Artificial Intelligence with Unreal Engine

Hands On Artificial Intelligence with Unreal Engine
Author: Francesco Sapio
Publsiher: Packt Publishing Ltd
Total Pages: 552
Release: 2019-04-25
ISBN: 1788831640
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence with Unreal Engine Book Excerpt:

Learn to build intelligent and responsive Non-Player Characters for your games with Unreal Engine Game AI. Key Features Understand the built-in AI systems in Unreal Engine for building intelligent games Leverage the power of Unreal Engine 4 programming to create game AI that focuses on motion, animation, and tactics Learn to profile, visualize, and debug your Game AI for checking logic and optimizing performance Book Description Learning how to apply artificial intelligence ( AI ) is crucial and can take the fun factor to the next level, whether you're developing a traditional, educational, or any other kind of game. If you want to use AI to extend the life of your games and make them challenging and more interesting, this book is for you. The book starts by breaking down AI into simple concepts to get a fundamental understanding of it. Using a variety of examples, you will work through actual implementations designed to highlight key concepts and features related to game AI in UE4. You will learn to work through the built-in AI framework in order to build believable characters for every game genre (including RPG, Strategic, Platform, FPS, Simulation, Arcade, and Educational). You will learn to configure the Navigation, Environmental Querying, and Perception systems for your AI agents and couple these with Behavior Trees, all accompanied with practical examples. You will also explore how the engine handles dynamic crowds. In the concluding chapters, you will learn how to profile, visualize, and debug your AI systems to correct the AI logic and increase performance. By the end of the book, your AI knowledge of the built-in AI system in Unreal will be deep and comprehensive, allowing you to build powerful AI agents within your projects. What you will learn Get an in-depth knowledge about all the AI Systems within Unreal Engine Create complex AIs, understanding the art of designing and developing Behavior Tree Learn how to perform Environmental Queries (EQS) Master the Navigation, Perception, and Crowd Systems Profile and Visualize the AI Systems with powerful debugging tools Extend every AI and Debug system with custom nodes and functions Who this book is for Hands-On Artificial Intelligence with Unreal Engine is for you if you are a game developer with a bit experience in Unreal Engine, and now want to understand and implement believable game AI within Unreal Engine. The book will be both in Blueprint and C++, allowing people from every background to enjoy the book. Whether you're looking to build your first game or expand your knowledge to the edge as a Game AI Programmer, you will find plenty of exciting information and examples of game AI in terms of concepts and implementation, including how to extend some of these systems.

Hands On Artificial Intelligence on Amazon Web Services

Hands On Artificial Intelligence on Amazon Web Services
Author: Subhashini Tripuraneni,Charles Song
Publsiher: Packt Publishing Ltd
Total Pages: 426
Release: 2019-10-04
ISBN: 1789531470
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence on Amazon Web Services Book Excerpt:

Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly Key Features Explore popular machine learning and deep learning services with their underlying algorithms Discover readily available artificial intelligence(AI) APIs on AWS like Vision and Language Services Design robust architectures to enable experimentation, extensibility, and maintainability of AI apps Book Description From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you’ll work through hands-on exercises and learn to use these services to solve real-world problems. You’ll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You’ll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you’ll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you’ll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. What you will learn Gain useful insights into different machine and deep learning models Build and deploy robust deep learning systems to production Train machine and deep learning models with diverse infrastructure specifications Scale AI apps without dealing with the complexity of managing the underlying infrastructure Monitor and Manage AI experiments efficiently Create AI apps using AWS pre-trained AI services Who this book is for This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected.

Hands On Artificial Intelligence for Banking

Hands On Artificial Intelligence for Banking
Author: Jeffrey Ng,Subhash Shah
Publsiher: Packt Publishing Ltd
Total Pages: 240
Release: 2020-07-10
ISBN: 1788833961
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence for Banking Book Excerpt:

Delve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python Key Features Understand how to obtain financial data via Quandl or internal systems Automate commercial banking using artificial intelligence and Python programs Implement various artificial intelligence models to make personal banking easy Book Description Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You’ll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you’ll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you’ll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you’ll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you’ll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you’ll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI. What you will learn Automate commercial bank pricing with reinforcement learning Perform technical analysis using convolutional layers in Keras Use natural language processing (NLP) for predicting market responses and visualizing them using graph databases Deploy a robot advisor to manage your personal finances via Open Bank API Sense market needs using sentiment analysis for algorithmic marketing Explore AI adoption in banking using practical examples Understand how to obtain financial data from commercial, open, and internal sources Who this book is for This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.

Python Machine Learning

Python Machine Learning
Author: James Deep
Publsiher: Unknown
Total Pages: 131
Release: 2019-11-08
ISBN: 9781705586686
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Python Machine Learning Book Excerpt:

If you are ready to know the link between Python Programming and Machine Learning, then keep reading. The concept of Artificial Intelligence is regarded by many as the way of the future. It covers vast areas of study and complements almost every aspect of human life. The evolution of intelligent machines has been on the rise as experts try to outsmart each other in innovation. Many business models, health organizations, government units, and many more, have adopted one or two practices that incorporate automation into their daily activities. As part of Artificial Intelligence, Machine Learning has seen significant applications across significant sectors of the economies of the world. To date, almost every aspect of our life has elements of Machine Learning. From the phones we use to the retail stores we do our shopping at, the areas covered by Machine Learning applications are drastically increasing by the day. This technique has helped the developers of software to create high-tech apps that predict changes in the market, sort large amounts of data, and offer solutions to major real-world problems. As much the trends are evident on the ground, the theoretical perspective remains an isolated area to many. Scaling through Machine Learning requires some knowledge of programming. In general terms, you need a platform to gain an understanding of the topic and hone your skills in the same. Python Machine Learning covers the concept of Machine Learning, in a detailed but well elaborate language of presentation. The topic may not be simple but is very worthwhile as long as you understand the fundamental concepts that underlie Machine Learning. Inside this book you will find Types of ML Use of Python in Machine Learning Essential Libraries for ML Regression Analysis Decision Trees The Perceptron Random Forest Algorithms K-Nearest Neighbors (KNN) ...and many more amazing and interesting topics! This book takes readers on a knowledge trip through solved examples, tips, tricks, and visualized content. It will not only create an appetite for more but also give readers what they need to know about Machine Learning, all these in a small volume for easy reading. Want to know more? Scroll to the top of the page and click the "buy now" button!

Python Machine Learning for Beginners

Python Machine Learning for Beginners
Author: Ai Publishing
Publsiher: Unknown
Total Pages: 302
Release: 2020-10-23
ISBN: 9781734790153
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Python Machine Learning for Beginners Book Excerpt:

Python Machine Learning for BeginnersMachine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay.Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing and salesYou name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future.But what does a Machine Learning professional do?A Machine Learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast.How Is This Book Different?AI Publishing strongly believes in learning by doing methodology. With this in mind, we have crafted this book with care. You will find that the emphasis on the theoretical aspects of machine learning is equal to the emphasis on the practical aspects of the subject matter.You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science.Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques.When you buy this book, your learning journey becomes so much easier. The reason is you get instant access to all the related learning material presented with this book--references, PDFs, Python codes, and exercises--on the publisher's website. All this material is available to you at no extra cost. You can download the ML datasets used in this book at runtime, or you can access them via the Resources/Datasets folder.You'll also find the short course on Python programming in the second chapter immensely useful, especially if you are new to Python. Since this book gives you access to all the Python codes and datasets, you only need access to a computer with the internet to get started. The topics covered include: Introduction and Environment Setup Python Crash Course Python NumPy Library for Data Analysis Introduction to Pandas Library for Data Analysis Data Visualization via Matplotlib, Seaborn, and Pandas Libraries Solving Regression Problems in ML Using Sklearn Library Solving Classification Problems in ML Using Sklearn Library Data Clustering with ML Using Sklearn Library Deep Learning with Python TensorFlow 2.0 Dimensionality Reduction with PCA and LDA Using Sklearn Click the BUY NOW button to start your Machine Learning journey.

Machine Learning for Beginners

Machine Learning for Beginners
Author: William J Ford
Publsiher: Unknown
Total Pages: 200
Release: 2020-02-18
ISBN: 1928374650XXX
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Machine Learning for Beginners Book Excerpt:

You Are About To Start Your Journey To Understanding Machine Learning Like The Back Of Your Hand And Use It To Your Advantage! If you've always wanted to learn how computers are able to perform some complex things like suggesting which products to buy to different customers depending on their buying behavior and much more, but you've never pictured yourself enrolling in a computer science class to study everything from scratch, then keep reading... Are you already tired about your business' poor performance or your limited ability to take advantage of modern technology to make your life easier because you don't understand the technology that every other successful person around you is leveraging every day? Have you tried using pre-built computer software to optimize your business but you never get the output you desire? Do you want to stop spending too much money on tech experts to assist you with tasks that you can do yourself with a little effort to learn, and increase efficiency? If so, then you've come to the right place. You see, having a successful online business or improving your knowledge about computer systems as regards to making accurate predictions for whatever goal doesn't have to be difficult- even if you are not ready to enroll for a computer science or IT course. In fact, it's easier than you think. One article published in Elite Data Science proves that machine learning can help us lead happier and healthier lives, especially with the recent breakthroughs in deep learning (that involves imitation of brain neurons). Another one published in Analytics Training asserts that learning machine learning is one of the best ways to guarantee success in many areas of the modern world, including business. Another article in Towards Data Science asserts that employing machine learning in manufacturing is the best way to improve efficiency, save money and time. That means that understanding machine learning, that tiny part of Artificial intelligence, can impact your daily life and businesses greatly. The question is.... Where do you even start? How do you build your understanding of machine learning to a point where you can start using it to make your life better? What are the critical things you need to learn about machine learning to get started as a beginner? What areas of your life can you apply your knowledge of machine learning? If you have these and other related questions, this book is for you so keep reading. Here's just a tiny fraction of what you'll discover in this book: The history of machine learning What machine learning can do for your business The machine learning algorithms How to develop a machine learning model from start to finish How neural networks work in machine learning The auto-encoders What you need to know about EM algorithm and how it is applied Logistic regression for machine learning The theory and setup in deep learning with tensorflow Natural language processing Data cleansing ...and much, much more! Take a second to imagine how you'd feel understanding how to can control a computer system to deliver output as you desire, without hiring an "expert", or at least understanding how computers make predictions. If you really want to find out how life would be once you know how to harness the power of modern technology to do anything you want, even if you are a complete beginner, Scroll up and click Buy Now With 1-Click or Buy Now to get started!

Python Machine Learning from Scratch

Python Machine Learning from Scratch
Author: Jonathan Adam
Publsiher: Createspace Independent Publishing Platform
Total Pages: 130
Release: 2016-08-24
ISBN: 9781725929982
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Python Machine Learning from Scratch Book Excerpt:

***** BUY NOW (will soon return to 25.89 $)******Free eBook for customers who purchase the print book from Amazon****** Are you thinking of learning more about Machine Learning using Python? (For Beginners) This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses.To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Step By Step Guide and Visual Illustrations and Examples This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using machine learning.Instead of tough math formulas, this book contains several graphs and images which detail all important Machine Learning concepts and their applications. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of machine learning. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Supervised Learning Algorithms Unsupervised Learning Algorithms Semi-supervised Learning Algorithms Reinforcement Learning Algorithms Overfitting and underfitting correctness The Bias-Variance Trade-off Feature Extraction and Selection A Regression Example: Predicting Boston Housing Prices Import Libraries: How to forecast and Predict Popular Classification Algorithms Introduction to K Nearest Neighbors Introduction to Support Vector Machine Example of Clustering Running K-means with Scikit-Learn Introduction to Deep Learning using TensorFlow Deep Learning Compared to Other Machine Learning Approaches Applications of Deep Learning How to run the Neural Network using TensorFlow Cases of Study with Real Data Sources & References Frequently Asked Questions Q: Is this book for me and do I need programming experience?A: If you want to smash Machine Learning from scratch, this book is for you. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK.Q: Does this book include everything I need to become a Machine Learning expert?A: Unfortunately, no. This book is designed for readers taking their first steps in Machine Learning and further learning will be required beyond this book to master all aspects of Machine Learning.Q: Can I have a refund if this book is not fitted for me?A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at [email protected] Sciences Company offers you a free eBooks at http://aisciences.net/free/

AI Crash Course

AI Crash Course
Author: Hadelin de Ponteves
Publsiher: Packt Publishing Ltd
Total Pages: 360
Release: 2019-11-29
ISBN: 1838645551
Category: Computers
Language: EN, FR, DE, ES & NL

AI Crash Course Book Excerpt:

This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. Key Features Roll up your sleeves and start programming AI models No math, data science, or machine learning background required Packed with hands-on examples, illustrations, and clear step-by-step instructions 5 hands-on working projects put ideas into action and show step-by-step how to build intelligent software Book Description AI is changing the world – and with this book, anyone can start building intelligent software! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Taking a graduated approach that starts with the basics before easing readers into more complicated formulas and notation, Hadelin helps you understand what you really need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming: Google Colab Python TensorFlow Keras PyTorch AI Crash Course teaches everyone to build an AI to work in their applications. Once you’ve read this book, you’re only limited by your imagination. What you will learn Master the key skills of deep learning, reinforcement learning, and deep reinforcement learning Understand Q-learning and deep Q-learning Learn from friendly, plain English explanations and practical activities Build fun projects, including a virtual-self-driving car Use AI to solve real-world business problems and win classic video games Build an intelligent, virtual robot warehouse worker Who this book is for If you want to add AI to your skillset, this book is for you. It doesn’t require data science or machine learning knowledge. Just maths basics (high school level).

Machine Learning For Beginners

Machine Learning For Beginners
Author: Scott Chesterton
Publsiher: Unknown
Total Pages: 150
Release: 2019-07-19
ISBN: 9781081534059
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Machine Learning For Beginners Book Excerpt:

**Buy the paperback version of this book and get the kindle book version for FREE** People often gets confused by words like Machine Learning, Artificial Intelligence or Deep Learning. Raise Your hand if you are among them. I'm sure that you heard several times people talking about machine learning but you only have a vague idea of what it is, isn't it? Don't worry, you are not the only one. This book is here to help those readers who want to understand machine learning in a simple language. By reading Machine Learning for beginners you will probably not become a pro in this field but you will no longer be a novice and that's for sure! With Machine Learning for beginners you will discover: The basics of Machine Learning in detail with daily life examples; The different algorithm models and computing software platforms used in Machine Learning and their practical applications; How Machine Learning applications affect in the real-world and in different fields. Interesting notes on artificial intelligence and deep learning to better understand these new crucial technologies. If you have no technical background but you are willing to get familiar with machine learning basics, scroll up to the page and push the BUY now button.

Machine Learning For Beginners

Machine Learning For Beginners
Author: Declan Mellor
Publsiher: Unknown
Total Pages: 104
Release: 2020-04-03
ISBN: 1928374650XXX
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Machine Learning For Beginners Book Excerpt:

Interested in the field of Artificial Intelligent? Then this book is for you!This book has been designed to learn complex theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of AI. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This guide is fun and exciting, but at the same time we dive deep into different aspects of AI. Moreover, the book is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. This book includes Python code templates which you can download and use on your own projects. Anyone interested in Artificial Intelligence Any students in college who want to start a career in Data Science Anyone who want to create added value to their business by using AI Anyone who want to kickstart their Artificial Intelligence journey See you Inside

Python Machine Learning for Beginners

Python Machine Learning for Beginners
Author: AI OU
Publsiher: Unknown
Total Pages: 301
Release: 2021
ISBN: 9781801814805
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Python Machine Learning for Beginners Book Excerpt:

This course lays the foundations for both a theoretical and practical understanding of machine learning and artificial intelligence, utilizing Python as a beginner-friendly introduction and invitation to further study Key Features A crash course in Python programming Interactive, guided practice through a series of machine learning exercises Instant access to PDFs, Python codes, and exercises from the publisher's website at no extra cost Book Description Machine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay. Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing, and sales. You name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future. But what does a machine learning professional do? A machine learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast. You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science. Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques. By the end of this course, you will have a firm grasp on the theoretical foundations of machine learning and artificial intelligence as well as having explored and practiced various real-world applications through Python. The code bundle for this course is available at https://www.aispublishing.net/nlp-crash-course1603576259757 What you will learn Get up to speed with Python programming Explore Python NumPy and Pandas libraries for data analysis Practice data visualization via Matplotlib, Seaborn, and Pandas libraries Solve regression problems in ML using Sklearn library Solve classification problems in ML using Sklearn library Study data clustering with ML using Sklearn library Cover deep learning with Python TensorFlow 2.0 Perform dimensi...

Python Machine Learning

Python Machine Learning
Author: Computer Programming Academy
Publsiher: Unknown
Total Pages: 212
Release: 2020-02-08
ISBN: 1928374650XXX
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Python Machine Learning Book Excerpt:

Would you like to learn how to use Python to generate machine learning models but you think it would be too difficult? Or perhaps you want to automate simple things with your computer but you don't know how to do it? Here's the deal... As a beginner you might think that programming is complex... Learning artificial intelligence coding can take months, and the possibility to give up before mastering it could be high. So, if you have a project to develop you could think on hiring a professional developer to shorten the time. This may seem like a good solution but it is certainly very expensive and if the developer you chose doesn't perform a proper job you still have to pay for it. The best solution is to follow a complete programming manual with hands-on projects and practical exercises. Computer Programming Academy structured this guide as a course with seven chapters for seven days and studied special exercises for each section to apply what you have learned step-by-step. This protocol, tested on both total beginners and people who were already familiar with coding, takes advantage of the principle of diving, concentrating learning in one week. The result of this method has been one for both categories of students: the content of the course was learned faster and remembered longer respect the average. Inside this book, you will go through a first section in which fundamental and basic notions of deep learning are discussed, to get to the next chapters crafted specifically to help you learn advanced coding concepts required to develop training data sets for the production of successful machine learning models. In the detail, you will learn: Why Python is considered the fundamental tool for machine learning Deep understanding of the significance of machine learning in our daily lives and why you cannot ignored its importance in 2020 12 machine learning models that you must study as a beginner The most common mistakes to avoid when you start building machine learning models with Python Step-by-step instructions to install required packages to set up a machine learning coding environment The algorithms that will make your life easier while coding artificial intelligence A proven strategy to process raw data to generate high quality training data sets A simple method to build the desired machine learning model in less than 7 days The 2 main libraries you need implementing to develop a neural network Exercises and quizzes at the end of every chapter to review immediately what you've learned Extra content that you will appreciate as curious technology enthusiast Why is this book different? Most of the books on the market only take a brief look into machine learning, showing some of the topics but never going deep concretely. The best way to learn machine learning with Python is by doing and with this manual you will work through applicable projects in order to solidify your knowledge and obtain a huge sense of achievement. This is what this guide offers to you, even if you're completely new to programming in 2020 or you are just looking to widen your skills as programmer. Would You Like To Know More? Scroll up to the top of the page and select the BUY NOW button. The key to become a Python master is one click away!

Machine Learning for Kids

Machine Learning for Kids
Author: Dale Lane
Publsiher: No Starch Press
Total Pages: 392
Release: 2021-01-19
ISBN: 1718500572
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning for Kids Book Excerpt:

A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+

Exploring Machine Learning A Beginners Perspective

Exploring Machine Learning  A Beginners Perspective
Author: Dr. Raghuram Bhukya
Publsiher: Horizon Books ( A Division of Ignited Minds Edutech P Ltd)
Total Pages: 135
Release: 2021-04-20
ISBN: 9391150012
Category: Computers
Language: EN, FR, DE, ES & NL

Exploring Machine Learning A Beginners Perspective Book Excerpt:

Machine learning is a field of Artificial intelligence that provides algorithms those can learn and improve from experiences. Machine learning algorithms are turned as integral parts of today’s digital life. Its applications include recommender systems, targeted campaigns, text categorization, computer vision and auto security systems etc. Machine learning also considered as essential part of data science due to its capability of providing predictive analytics, capability in handling variety of data and suitability for big data applications. Its capability for predictive analytics resulted of its general structure that is building statistical models out of training data. In other hand easy scalability advantage of machine learning algorithms is making them to be suitable for big data applications. The different types of learning algorithms includes supervised learning, unsupervised learning, reinforcement learning, feature learning, rule based learning, Robot or expert system learning, sparse dictionary and anomaly detection. These learning algorithms can be realized by computing models artificial neural networks, decision trees, support vector machines, regression analysis, Bayesian networks, Genetic algorithms and soft computing. The familiar tools to implement machine learning algorithms include Python, R, Matlab, Scala, Clojure and Ruby. Involving of such open source programming languages, tools and social network communities makes the machine learning most progressing filed of computer science. The machine learning life cycle includes defining project objectives, explore the types and format, modeling data to fit for machine learning algorithms, deciding suitable machine learning model and implement and decide best result from data for decision making. These days, machine learning is observing great interest by the society and it has turned as one of the significant responsibility of top level managers to transform their business in the profitable means by exploring its basic functionalities. The world is at the sheer of realizing a situation where machines will work in agreement with human being to work together, operation, and advertise their services in a novel way which is targeted, valuable, and well-versed. In order to achieve this, they can influence machine learning distinctiveness. Dr. Raghuram Bhukya

Machine Learning

Machine Learning
Author: Gabriel Rhys
Publsiher: Createspace Independent Publishing Platform
Total Pages: 178
Release: 2017-10-18
ISBN: 9781978373884
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Machine Learning Book Excerpt:

Can Machines Really Learn?Machine learning (ML) is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning has become an essential pillar of IT in all aspects, even though it has been hidden in the recent past. We are increasingly being surrounded by several machine learning-based apps across a broad spectrum of industries. From search engines to anti-spam filters to credit card fraud detection systems, list of machine learning applications is ever-expanding in scope and applications. The goal of this book is to provide you with a hands-on, project-based overview of machine learning systems and how they are applied over a vast spectrum of applications that underpins AI technology from Absolute Beginners to Experts.This book is a fast-paced, thorough introduction to Machine Learning that will have you writing programs, solving problems, and making things that work in no time.This book presents algorithms and approaches in such a way that grounds them in larger systems as you learn about a variety of topics, including: Supervised and Unsupervised learning methods Artificial Neural Networks Hands-on projects based on Real-world applications Bayesian learning method Reinforcement learning And much more By the end of this book, you should have a strong understanding of machine learning so that you can pursue any further and more advanced learning. Learning Outcomes: By the end of this book, you will be able to: Identify potential applications of machine learning in practice Describe the core differences in analyses enabled by regression, classification, and clustering Select the appropriate machine learning task for a potential application Apply regression, classification, and clustering Represent your data as features to serve as input to machine learning models Utilize a dataset to fit a model to analyze new data Build an end-to-end application that uses machine learning at its core Implement these techniques in Python If you've been thinking seriously about digging into ML, this book will get you up to speed. Why wait any longer?

Introduction to Machine Learning with Python

Introduction to Machine Learning with Python
Author: David James
Publsiher: Createspace Independent Publishing Platform
Total Pages: 234
Release: 2018-08-25
ISBN: 9781726230872
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Introduction to Machine Learning with Python Book Excerpt:

***** BUY NOW (will soon return to 24.78 $)******Free eBook for customers who purchase the print book from Amazon****** Are you thinking of learning more about Machine Learning using Python? (For Beginners) This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses. To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Step By Step Guide and Visual Illustrations and Examples This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using machine learning. Instead of tough math formulas, this book contains several graphs and images which detail all important Machine Learning concepts and their applications. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of machine learning. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Supervised Learning Algorithms Unsupervised Learning Algorithms Semi-supervised Learning Algorithms Reinforcement Learning Algorithms Overfitting and underfitting correctness The Bias-Variance Trade-off Feature Extraction and Selection A Regression Example: Predicting Boston Housing Prices Import Libraries: How to forecast and Predict Popular Classification Algorithms Introduction to K Nearest Neighbors Introduction to Support Vector Machine Example of Clustering Running K-means with Scikit-Learn Introduction to Deep Learning using TensorFlow Deep Learning Compared to Other Machine Learning Approaches Applications of Deep Learning How to run the Neural Network using TensorFlow Cases of Study with Real Data Sources & References Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: If you want to smash Machine Learning from scratch, this book is for you. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK. Q: Does this book include everything I need to become a Machine Learning expert? A: Unfortunately, no. This book is designed for readers taking their first steps in Machine Learning and further learning will be required beyond this book to master all aspects of Machine Learning. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at [email protected] If you need to see the quality of our job, AI Sciences Company offering you a free eBook in Machine Learning with Python written by the data scientist Alain Kaufmann at http: //aisciences.net/free-books/