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 FeaturesUnderstand how to obtain financial data via Quandl or internal systemsAutomate commercial banking using artificial intelligence and Python programsImplement various artificial intelligence models to make personal banking easyBook 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 learnAutomate commercial bank pricing with reinforcement learningPerform technical analysis using convolutional layers in KerasUse natural language processing (NLP) for predicting market responses and visualizing them using graph databasesDeploy a robot advisor to manage your personal finances via Open Bank APISense market needs using sentiment analysis for algorithmic marketingExplore AI adoption in banking using practical examplesUnderstand how to obtain financial data from commercial, open, and internal sourcesWho 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.

Advances in Financial Machine Learning

Advances in Financial Machine Learning
Author: Marcos Lopez de Prado
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2018-02-21
ISBN: 1119482089
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Advances in Financial Machine Learning Book Excerpt:

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Hands On Deep Learning for Finance

Hands On Deep Learning for Finance
Author: Luigi Troiano,Pravesh Kriplani,Elena Mejuto Villa
Publsiher: Unknown
Total Pages: 442
Release: 2020-02-28
ISBN: 9781789613179
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Deep Learning for Finance Book Excerpt:

Hands On Python for Finance

Hands On Python for Finance
Author: Krish Naik
Publsiher: Unknown
Total Pages: 378
Release: 2019-03-29
ISBN: 9781789346374
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Python for Finance Book Excerpt:

Learn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras Key Features Understand Python data structure fundamentals and work with time series data Use popular Python libraries including TensorFlow, Keras, and SciPy to deploy key concepts in quantitative finance Explore various Python programs and learn finance paradigms Book Description Python is one of the most popular languages used for quantitative finance. With this book, you'll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management. The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you'll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and optimize your portfolio by implementing Markowitz Portfolio Optimization. Sections on regression analysis methodology will help you to value assets and understand the relationship between commodity prices and business stocks. In addition to this, you'll be able to forecast stock prices using Monte Carlo simulation. The book will also highlight forecast models that will show you how to determine the price of a call option by analyzing price variation. You'll also use deep learning for financial data analysis and forecasting. In the concluding chapters, you will create neural networks with TensorFlow and Keras for forecasting and prediction. By the end of this book, you will be equipped with the skills you need to perform different financial analysis tasks using Python What you will learn Clean financial data with data preprocessing Visualize financial data using histograms, color plots, and graphs Perform time series analysis with pandas for forecasting Estimate covariance and the correlation between securities and stocks Optimize your portfolio to understand risks when there is a possibility of higher returns Calculate expected returns of a stock to measure the performance of a portfolio manager Create a prediction model using recurrent neural networks (RNN) with Keras and TensorFlow Who this book is for This book is ideal for aspiring data scientists, Python developers and anyone who wants to start performing quantitative finance using Python. You can also make this beginner-level guide your first choice if you're looking to pursue a career as a financial analyst or a data analyst. Working knowledge of Python programming language is necessary.

Hands On Cybersecurity for Finance

Hands On Cybersecurity for Finance
Author: Dr. Erdal Ozkaya,Milad Aslaner
Publsiher: Packt Publishing Ltd
Total Pages: 308
Release: 2019-01-31
ISBN: 178883173X
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Cybersecurity for Finance Book Excerpt:

This is a comprehensive guide to help you understand the current threats faced by the financial cyberspace and how to go about it and secure your financial landscape. The book will take you on a journey from identifying the attackers to securing your financial transactions and assets. The book then take you through the updates needed for ...

Machine Learning and Artificial Intelligence with Industrial Applications

Machine Learning and Artificial Intelligence with Industrial Applications
Author: Diego Carou,Antonio Sartal,J. Paulo Davim
Publsiher: Springer Nature
Total Pages: 216
Release: 2022
ISBN: 3030910067
Category: Artificial intelligence
Language: EN, FR, DE, ES & NL

Machine Learning and Artificial Intelligence with Industrial Applications Book Excerpt:

This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.

Machine Learning

Machine Learning
Author: Anonim
Publsiher: BoD – Books on Demand
Total Pages: 152
Release: 2021-12-22
ISBN: 183969484X
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning Book Excerpt:

Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses–cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real-world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.

The AI Book

The AI Book
Author: Ivana Bartoletti,Anne Leslie,Shân M. Millie
Publsiher: John Wiley & Sons
Total Pages: 304
Release: 2020-04-27
ISBN: 1119551900
Category: Business & Economics
Language: EN, FR, DE, ES & NL

The AI Book Book Excerpt:

Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

Artificial Intelligence in Finance

Artificial Intelligence in Finance
Author: Yves Hilpisch
Publsiher: O'Reilly Media
Total Pages: 478
Release: 2020-10-14
ISBN: 1492055409
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Finance Book Excerpt:

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Artificial Intelligence for Sustainable Finance and Sustainable Technology

Artificial Intelligence for Sustainable Finance and Sustainable Technology
Author: Abdalmuttaleb M. A. Musleh Al-Sartawi
Publsiher: Springer Nature
Total Pages: 637
Release: 2021
ISBN: 3030934640
Category: Artificial intelligence
Language: EN, FR, DE, ES & NL

Artificial Intelligence for Sustainable Finance and Sustainable Technology Book Excerpt:

This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.

Blockchain Artificial Intelligence and Financial Services

Blockchain  Artificial Intelligence and Financial Services
Author: Sean Stein Smith
Publsiher: Springer Nature
Total Pages: 263
Release: 2019-11-15
ISBN: 3030297616
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Blockchain Artificial Intelligence and Financial Services Book Excerpt:

Blockchain technology and artificial intelligence (AI) have the potential to transform how the accounting and financial services industries engage with the business, stakeholder and consumer communities. Presenting a blend of technical analysis with current and future applications, this book provides professionals with an action plan to embrace and move forward with these new technologies in financial and accounting organizations. It is written in a conversational style that is unbiased and objective, replacing jargon and technical details with real world case examples.

An Introduction to Machine Learning in Quantitative Finance

An Introduction to Machine Learning in Quantitative Finance
Author: Hao Ni,Jinsong Zheng
Publsiher: Advanced Textbooks In Mathematics
Total Pages: 265
Release: 2021
ISBN: 9781786349644
Category: Finance
Language: EN, FR, DE, ES & NL

An Introduction to Machine Learning in Quantitative Finance Book Excerpt:

In today's world, we are increasingly exposed to the words "machine learning" (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it. An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authors Provide a systematic and rigorous introduction to supervised, unsupervised and reinforcement learning by establishing essential definitions and theorems. Dive into various types of neural networks, including artificial nets, convolutional nets, recurrent nets and recurrent reinforcement learning. Summarize key contents of each section in the tables as a cheat sheet. Include ample examples of financial applications. Showcase how to tackle an exemplar ML project on financial data end-to-end. Supplement Python codes of all the methods/examples in a GitHub repository. Featured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data! The Python codes contained within An Introduction to Machine Learning in Quantitative Finance have been made publicly available on the author's GitHub: https: //github.com/deepintomlf/mlfbook.git

The Essentials of Machine Learning in Finance and Accounting

The Essentials of Machine Learning in Finance and Accounting
Author: Mohammad Zoynul Abedin,M. Kabir Hassan,Petr Hajek,Mohammed Mohi Uddin
Publsiher: Routledge
Total Pages: 258
Release: 2021-06-21
ISBN: 1000394123
Category: Business & Economics
Language: EN, FR, DE, ES & NL

The Essentials of Machine Learning in Finance and Accounting Book Excerpt:

Th­is book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. ­These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. ­The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. Th­is book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

Applications of Artificial Intelligence in Business and Finance

Applications of Artificial Intelligence in Business and Finance
Author: Vikas Garg,Shalini Aggarwal,Pooja Tiwari,Prasenjit Chatterjee
Publsiher: CRC Press
Total Pages: 272
Release: 2021-12-23
ISBN: 1000290417
Category: Science
Language: EN, FR, DE, ES & NL

Applications of Artificial Intelligence in Business and Finance Book Excerpt:

As transactions and other business functions move online and grow more popular every year, the finance and banking industries face increasingly complex data management and identity theft and fraud issues. AI can bring many financial and business functions to the next level, as systems using deep learning technologies are able to analyze patterns and spot suspicious behavior and potential fraud. In this volume, the focus is on the application of artificial intelligence in finance, business, and related areas. The book presents a selection of chapters presenting cutting-edge research on current business practices in finance and management. Topics cover the use of AI in e-commerce systems, financial services, fraud prevention, identifying loan-eligible customers, online business, Facebook social commerce, insurance industry, online marketing, and more.

Enterprise Applications Markets and Services in the Finance Industry

Enterprise Applications  Markets and Services in the Finance Industry
Author: Benjamin Clapham,Jascha-Alexander Koch
Publsiher: Springer Nature
Total Pages: 117
Release: 2020-11-25
ISBN: 3030644669
Category: Computers
Language: EN, FR, DE, ES & NL

Enterprise Applications Markets and Services in the Finance Industry Book Excerpt:

This book constitutes the revised selected papers from the 10th International Workshop on Enterprise Applications, Markets and Services in the Finance Industry, FinanceCom 2020, held in Helsinki, Finland, in August 2020. Due to the COVID-19 pandemic the conference took place virtually. The 6 full papers presented together with 1 extended abstract in this volume were carefully reviewed and selected from a total of 14 submissions to the workshop.They are grouped in topical sections named Machine Learning Applications in Trading and Financial Markets, Fraud Detection and Information Generation in Finance, and Alternative Trading and Investment Offerings by FinTechs.The workshop spans multiple disciplines, including analytical, technical, service, economic, sociological and behavioral sciences.

Economic and Policy Implications of Artificial Intelligence

Economic and Policy Implications of Artificial Intelligence
Author: Domenico Marino,Melchiorre A. Monaca
Publsiher: Springer Nature
Total Pages: 169
Release: 2020-05-20
ISBN: 3030453405
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Economic and Policy Implications of Artificial Intelligence Book Excerpt:

This book presents original research articles addressing various aspects of artificial intelligence as applied to economics, law, management and optimization. The topics discussed include economics, policies, finance, law, resource allocation strategies and information technology. Combining the input of contributing professors and researchers from Italian and international universities, the book will be of interest to students, researchers and practitioners, as well as members of the general public interested in the economic and policy implications of artificial intelligence.

Artificial Intelligence and Big Data for Financial Risk Management

Artificial Intelligence and Big Data for Financial Risk Management
Author: Noura Metawa,M. Kabir Hassan,Saad Metawa
Publsiher: Taylor & Francis
Total Pages: 249
Release: 2022-08-26
ISBN: 1000645274
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Big Data for Financial Risk Management Book Excerpt:

This book presents a collection of high-quality contributions on the state-of-the-art in Artificial Intelligence and Big Data analysis as it relates to financial risk management applications. It brings together, in one place, the latest thinking on an emerging topic and includes principles, reviews, examples, and research directions. The book presents numerous specific use-cases throughout, showing practical applications of the concepts discussed. It looks at technologies such as eye movement analysis, data mining or mobile apps and examines how these technologies are applied by financial institutions, and how this affects both the institutions and the market. This work introduces students and aspiring practitioners to the subject of risk management in a structured manner. It is primarily aimed at researchers and students in finance and intelligent big data applications, such as intelligent information systems, smart economics and finance applications, and the internet of things in a marketing environment.

Hands On Artificial Intelligence for Search

Hands On Artificial Intelligence for Search
Author: Devangini Patel
Publsiher: Packt Publishing Ltd
Total Pages: 124
Release: 2018-08-30
ISBN: 1789612470
Category: Computers
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence for Search Book Excerpt:

Make your searches more responsive and smarter by applying Artificial Intelligence to it Key Features Enter the world of Artificial Intelligence with solid concepts and real-world use cases Make your applications intelligent using AI in your day-to-day apps and become a smart developer Design and implement artificial intelligence in searches Book Description With the emergence of big data and modern technologies, AI has acquired a lot of relevance in many domains. The increase in demand for automation has generated many applications for AI in fields such as robotics, predictive analytics, finance, and more. In this book, you will understand what artificial intelligence is. It explains in detail basic search methods: Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search, which can be used to make intelligent decisions when the initial state, end state, and possible actions are known. Random solutions or greedy solutions can be found for such problems. But these are not optimal in either space or time and efficient approaches in time and space will be explored. We will also understand how to formulate a problem, which involves looking at it and identifying its initial state, goal state, and the actions that are possible in each state. We also need to understand the data structures involved while implementing these search algorithms as they form the basis of search exploration. Finally, we will look into what a heuristic is as this decides the quality of one sub-solution over another and helps you decide which step to take. What you will learn Understand the instances where searches can be used Understand the algorithms that can be used to make decisions more intelligent Formulate a problem by specifying its initial state, goal state, and actions Translate the concepts of the selected search algorithm into code Compare how basic search algorithms will perform for the application Implement algorithmic programming using code examples Who this book is for This book is for developers who are keen to get started with Artificial Intelligence and develop practical AI-based applications. Those developers who want to upgrade their normal applications to smart and intelligent versions will find this book useful. A basic knowledge and understanding of Python are assumed.

Artificial Intelligence and Islamic Finance

Artificial Intelligence and Islamic Finance
Author: Adel M. Sarea,Ahmed H. Elsayed,Saeed A. Bin-Nashwan
Publsiher: Routledge
Total Pages: 180
Release: 2021-12-31
ISBN: 100052812X
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Islamic Finance Book Excerpt:

This book provides a systematic overview of the current trends in research relating to the use of artificial intelligence in Islamic financial institutions (IFIs), across all organization of Islamic cooperation (OIC) countries. Artificial Intelligence and Islamic Finance discusses current and potential applications of artificial intelligence (AI) for risk management in Islamic finance. It covers various techniques of risk management, encompassing asset and liability management risk, credit, market, operational, liquidity risk, as well as regulatory and Shariah risk compliance within the financial industry. The authors highlight AI’s ability to combat financial crime such as monitoring trader recklessness, anti-fraud and anti-money laundering, and assert that the capacity of machine learning (ML) to examine large amounts of data allows for greater granular and profound analyses across a variety of Islamic financial products and services. The book concludes with practical limitations around data management policies, transparency, and lack of necessary skill sets within financial institutions. By adopting new methodological approaches steeped in an Islamic economic framework (e.g., analysing FinTech in the context of Shariah principles and Islamic values), it devises practical solutions and generates insightful knowledge, helping readers to understand and explore the role of technological enablers in the Islamic finance industry, such as RegTech and artificial intelligence, in providing better and Shariah-compliant services to customers through digital platforms. The book will attract a wide readership spanning Shariah scholars, academicians, and researchers as well as Islamic financial practitioners and policy makers.

Hands On Artificial Intelligence with TensorFlow

Hands On Artificial Intelligence with TensorFlow
Author: Amir Ziai,Ankit Dixit
Publsiher: Unknown
Total Pages: 582
Release: 2018-10-31
ISBN: 9781788998079
Category: Artificial intelligence
Language: EN, FR, DE, ES & NL

Hands On Artificial Intelligence with TensorFlow Book Excerpt:

Book Description Artificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more. Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques. In addition to this, the book covers advanced concepts, such as reinforcement learning, generative adversarial networks (GANs), and multimodal learning. Once you have grasped all this, you'll move on to exploring GPU computing and neuromorphic computing, along with the latest trends in quantum computing. You'll work through case studies that will help you examine AI applications in the important areas of computer vision, healthcare, and FinTech, and analyze their datasets. In the concluding chapters, you'll briefly investigate possible developments in AI that we can expect to see in the future. By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow. What you will learn Explore the core concepts of AI and its different approaches Use the TensorFlow framework for smart applications Implement various machine and deep learning algorithms with TensorFlow Design self-learning RL systems and implement generative models Perform GPU computing efficiently using best practices Build enterprise-grade apps for computer vision, NLP, and healthcare Who this book is for Hands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.