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
Genre: Computers
ISBN: 9781789531022

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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.

Machine Learning in Java

Machine Learning in Java
Author: AshishSingh Bhatia,Bostjan Kaluza
Publsiher: Packt Publishing Ltd
Total Pages: 300
Release: 2018-11-28
Genre: Computers
ISBN: 9781788473897

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Leverage the power of Java and its associated machine learning libraries to build powerful predictive models Key Features Solve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET libraries Practical examples, tips, and tricks to help you understand applied machine learning in Java Book Description As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data. What you will learn Discover key Java machine learning libraries Implement concepts such as classification, regression, and clustering Develop a customer retention strategy by predicting likely churn candidates Build a scalable recommendation engine with Apache Mahout Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts and algorithms Write your own activity recognition model for eHealth applications Who this book is for If you want to learn how to use Java's machine learning libraries to gain insight from your data, this book is for you. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications with ease. You should be familiar with Java programming and some basic data mining concepts to make the most of this book, but no prior experience with machine learning is required.

Artificial Intelligence

Artificial Intelligence
Author: Code Well Academy
Publsiher: Createspace Independent Publishing Platform
Total Pages: 150
Release: 2016-04-10
Genre: Electronic Book
ISBN: 1530826861

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Design the MIND of a Robotic Thinker! " Every chapter is very clearly described and all of the information was presented consistently. " - Amazon Customer " Within this book you'll find GREAT coding skills to learn. Here I've learned so much from reading this book. " - Stella Mill, from Amazon.com " This is the most complete and comprehensive book I read on a subject of Artificial Intelligence so far and it's very well written as well. " - Falli Conna, from Amazon.com * * INCLUDED BONUS: a Quick-start guide to Learning Ruby in less than a Day! * * How would you like to Create the Next AI bot? Artificial Intelligence. One of the most brilliant creations of mankind. No longer a sci-fi fantasy, but a realistic approach to making work more efficient and lives easier.And the best news? It's not that complicated after all Does it require THAT much advanced math? NO!And are you paying THOUSANDS of dollars just to learn this information? NO!Hundreds? Not even close. Within this book's pages, you'll find GREAT coding skills to learn - and more. Just some of the questions and topics include: - Complicated scheduling problem? Here's how to solve it. - How good are your AI algorithms? Analysis for Efficiency- How to interpret a system into logical code for the AI- How would an AI system would diagnose a system? We show you...- Getting an AI agent to solve problems for youand Much, much more!World-Class TrainingThis book breaks your training down into easy-to-understand modules. It starts from the very essentials of algorithms and program procedures, so you can write great code - even as a beginner!

Paging Dr Within

Paging Dr  Within
Author: Tom Garz
Publsiher: Tom Garz - TG Ideas LLC
Total Pages: 135
Release: 2020-03-22
Genre: Medical
ISBN: 9788835391319

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As a Patient - Would you like a "Patient Listener"? Are you tired of Medicine/Treatment "Trial and Error", at your expense? Are you tired of being shuffled from one Doctor to another? Do you want to "get better" and "stay better"? As a Doctor – Would you like more good information from Patients, relevant to their symptoms? Would you like to help Patients "get better" and "stay better"? Are you open to venturing out of your "comfort zone" in diagnosing and treating patients? Do you sometimes wonder if there is more to diagnosing/treating than what you were taught in Medical School? As a Health/Medical Innovator, Inventor, Engineer, Writer, other Creative Person – Are you looking for some new ideas? Would you like to "Interface" with the "Dr. Within" each of us? As an Insurance Company - Would you like to "pay out" less? If you answered yes to any of the above, maybe this book is for you. This book describes the Concepts of a "Patient Listener" and a "Super Symptom Checker" – Human, Computer, and/or Computer-Assisted Human – Considering the "Big Picture" around Health and/or Symptoms. This book is about 250 pages, a little over half written text. The remainder contains many Reference Links, from which you can build upon and learn from. The author of this book has set up Discussion Groups for this book to help others share, network, collaborate, etc. *** Use of the Information in this book may help the Patient, Doctor, and/or Others "Get Better". Some common Side Effects may include: A better understanding of what affects Health and Symptoms, Seeing the big picture surrounding Symptoms, Better health, less dependence on medication/treatment, generally "feeling better", Experiencing less perceived stress, more contentment with self and life, Perceiving more control of your life, in general, realizing there are always options no matter what, New insights on what could be done to make "it" better. Note - Continued Use of the Information in this book may result in "Staying Better". Ask your Doctor if "Getting Better" and "Staying Better" are right for you. :-)

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
Genre: Computers
ISBN: 9781788992268

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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 for Search

Hands On Artificial Intelligence for Search
Author: Devangini Patel
Publsiher: Packt Publishing Ltd
Total Pages: 124
Release: 2018-08-30
Genre: Computers
ISBN: 9781789612479

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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.

Mastering Java Machine Learning

Mastering Java Machine Learning
Author: Dr. Uday Kamath,Krishna Choppella
Publsiher: Packt Publishing Ltd
Total Pages: 556
Release: 2017-07-11
Genre: Computers
ISBN: 9781785888557

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Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects More than 15 open source Java tools in a wide range of techniques, with code and practical usage. More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. Apply machine learning to real-world data with methodologies, processes, applications, and analysis. Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Artificial Intelligence with Python

Artificial Intelligence with Python
Author: Prateek Joshi
Publsiher: Packt Publishing Ltd
Total Pages: 446
Release: 2017-01-27
Genre: Computers
ISBN: 9781786469670

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Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Artificial Intelligence with Python

Artificial Intelligence with Python
Author: Alberto Artasanchez,Prateek Joshi
Publsiher: Packt Publishing Ltd
Total Pages: 618
Release: 2020-01-31
Genre: Computers
ISBN: 9781839216077

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New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key Features Completely updated and revised to Python 3.x New chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineering Learn more about deep learning algorithms, machine learning data pipelines, and chatbots Book Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learn Understand what artificial intelligence, machine learning, and data science are Explore the most common artificial intelligence use cases Learn how to build a machine learning pipeline Assimilate the basics of feature selection and feature engineering Identify the differences between supervised and unsupervised learning Discover the most recent advances and tools offered for AI development in the cloud Develop automatic speech recognition systems and chatbots Apply AI algorithms to time series data Who this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.

Beginning Java 8 Games Development

Beginning Java 8 Games Development
Author: Wallace Jackson
Publsiher: Apress
Total Pages: 492
Release: 2014-12-04
Genre: Computers
ISBN: 9781484204153

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Beginning Java 8 Games Development, written by Java expert and author Wallace Jackson, teaches you the fundamentals of building a highly illustrative game using the Java 8 programming language. In this book, you'll employ open source software as tools to help you quickly and efficiently build your Java game applications. You'll learn how to utilize vector and bit-wise graphics; create sprites and sprite animations; handle events; process inputs; create and insert multimedia and audio files; and more. Furthermore, you'll learn about JavaFX 8, now integrated into Java 8 and which gives you additional APIs that will make your game application more fun and dynamic as well as give it a smaller foot-print; so, your game application can run on your PC, mobile and embedded devices. After reading and using this tutorial, you'll come away with a cool Java-based 2D game application template that you can re-use and apply to your own game making ambitions or for fun.

Practical Java Machine Learning

Practical Java Machine Learning
Author: Mark Wickham
Publsiher: Apress
Total Pages: 392
Release: 2018-10-23
Genre: Computers
ISBN: 9781484239513

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Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services. Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualization for Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data. After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java. What You Will LearnIdentify, organize, and architect the data required for ML projects Deploy ML solutions in conjunction with cloud providers such as Google and Amazon Determine which algorithm is the most appropriate for a specific ML problem Implement Java ML solutions on Android mobile devices Create Java ML solutions to work with sensor data Build Java streaming based solutionsWho This Book Is For Experienced Java developers who have not implemented machine learning techniques before.

Mobile Artificial Intelligence Projects

Mobile Artificial Intelligence Projects
Author: Karthikeyan NG,Arun Padmanabhan,Matt R. Cole
Publsiher: Packt Publishing Ltd
Total Pages: 312
Release: 2019-03-30
Genre: Computers
ISBN: 9781789347043

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Artificial intelligence (AI) is rapidly becoming the most popular topic in business and science. This book introduces AI concepts and their use cases with a hands-on and application-focused approach. We will cover a range of projects covering tasks such as automated reasoning, facial recognition, digital assistants, auto text generation, and more.

Programming Game AI by Example

Programming Game AI by Example
Author: Mat Buckland
Publsiher: Jones & Bartlett Learning
Total Pages: 495
Release: 2005
Genre: Computers
ISBN: 1556220782

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Provides an introduction to AI game techniques used in game programming.

Artificial Intelligence for Big Data

Artificial Intelligence for Big Data
Author: Anand Deshpande,Manish Kumar
Publsiher: Packt Publishing Ltd
Total Pages: 384
Release: 2018-05-22
Genre: Computers
ISBN: 9781788476010

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Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.

Hands On Artificial Intelligence for Android

Hands On Artificial Intelligence for Android
Author: Vasco Correia Veloso
Publsiher: BPB Publications
Total Pages: 394
Release: 2022-01-27
Genre: Computers
ISBN: 9789355510242

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Build machine learning models and train them to make Android applications much smarter. KEY FEATURES ● Learn by doing, training, and evaluating your own machine learning models. ● Includes pre-trained TensorFlow models for image processing. ● Explains practical use cases of artificial intelligence in Android. DESCRIPTION This book features techniques and real implementations of machine learning applications on Android phones. This book covers various developer tools, including TensorFlow and Google ML Kit. The book begins with a quick review of android application development fundamentals and a couple of Java and Kotlin implementations developed using the Android Studio integrated development environment. The book explores TensorFlow Lite and Google ML Kit, along with some of the most widely used machine learning techniques. The book covers real projects on TensorFlow, demonstrates how to collect photos with Camera X, and preprocess them with the Google ML Kit. It explains how to onboard the power of machine learning in Android applications that detect images, identify faces, and apply effects to photographs, among other things. These applications are constructed on top of TensorFlow models – some of which were created and trained by the reader – and then converted to TensorFlow Lite for mobile applications. After reading the book, the reader will be able to apply machine learning techniques to create Android applications and take their applications to the next level. This book can be a successful tool to deep dive into Data Science for all mobile programmers. WHAT YOU WILL LEARN ● Get well-versed with Android Development and the fundamentals of AI. ● Learn to set up the ML environment with hands-on knowledge of TensorFlow. ● Build, train, and evaluate Machine Learning models. ● Practice ML by working on real face verification and identification applications. ● Explore cutting-edge models such as GAN and RNN in detail. ● Experience the use of CameraX, SQLite, and Google ML Kit on Android. WHO THIS BOOK IS FOR This book is intended for android developers, application engineers, machine learning engineers, and anybody interested in infusing intelligent, inventive, and smart features into mobile phones. Readers should have a basic understanding of the Java programming language. TABLE OF CONTENTS 1. Building an Application with Android Studio and Java 2. Event Handling and Intents in Android 3. Building our Base Application with Kotlin and SQLite 4. An Overview of Artificial Intelligence and Machine Learning 5. Introduction to TensorFlow 6. Training a Model for Image Recognition with TensorFlow 7. Android Camera Image Capture with CameraX 8. Using the Image Recognition Model in an Android Application 9. Detecting Faces with the Google ML Kit 10. Verifying Faces in Android with TensorFlow Lite 11. Registering Faces in the Application 12. Image Processing with Generative Adversarial Networks 13. Describing Images with NLP