This book is designed for use as a primary introduction to Python and can be used as an introductory text or resource for professionals in the industry. The book has been divided into four sections. The first section deals with the language fundamentals, primarily the procedural part of the language, the second introduces the object-oriented paradigms. The third section deals with data structures, and the last are devoted to advanced topics like handling multi-dimensional arrays using NumPy and visualization using Matplotlib. Regular expressions and multi-threading have been introduced in the appendices.
- Lifetime access on eBooks with 450 pages
- Know more about data structures
- Gain in-depth treatment of topics such as classes, inheritance, BST & Numpy
- Do exercises for practice
- Review essential programming concepts
This video series will provide the viewer with some basic programming skills in NumPy and Pandas. The package includes thirteen videos with detailed instructions using code samples. Topics range from Introduction to NumPy and Pandas to NumPy arrays, vectors and operators, Pandas Dataframes, operations, and more. A supplemental video on using the Google Colaboratory is also included.
- Attain some basic programming skills in NumPy & Pandas
- Get 13 videos with detailed instructions using code samples.
- Understand a wide range of topics, from Introduction to Numpy & Pandas to Numpy arrays, vectors & operators
- Overview on Pandas Dataframes, operations & more
- Watch a supplemental video using Google Colaboratory
As part of the new Pocket Primer series, this book provides an overview of the major aspects and the source code to use Python 2. It covers the latest Python developments, built-in functions and custom classes, data visualization, graphics, databases, and more. It includes a companion disc with appendices, source code, and figures. This Pocket Primer is primarily for self-directed learners who want to learn Python 2, and it serves as a starting point for deeper exploration of Python programming.
- Lifetime access on eBooks with 200 pages
- Get a companion disc with appendices, source code & figures
- Attain materials that are devoted to Raspberry Pi, Roomba, JSON & Jython
- Know latest Python 2 developments, built-in functions & custom classes, data visualization, graphics, databases & more
- Gain a solid introduction to Python 2 via complete code samples
As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and sci-kit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2).
- Lifetime access on eBooks with 218 pages
- Practical introduction to Python, NumPy, Pandas & Matplotlib
- Learn about the fundamental aspects of TensorFlow 1.x
- Understand relevant NumPy/Pandas code samples that are typical in machine learning topics
- Get to know better some of the useful TensorFlow 1.x code samples for deep learning
- Get examples of TensorFlow Dataset APIs with lazy operators
- Gain companion files with all the source code examples
This book introduces programming concepts that use Python 3 as the target language. It follows a practical just-in-time presentation – the material is given to the student when it is needed. Many examples will be based on games because Python has become the language of choice for basic game development. Designed as a Year One textbook to introduce programming classes or for the hobbyist who wants to learn the fundamentals of programming, the text assumes no programming experience.
- Lifetime access on eBooks with 600 pages
- Discover programming concepts that use Python 3
- Know some examples based on video game development
- Know the 4-color throughout with game demos on the companion files
- Overview on computers & programming languages
- Learn how to write a good program
- Know how to communicate with the outside world
This book will guide you through the basic game development process using Python, covering game topics including graphics, sound, artificial intelligence, animation, game engines, etc. Real games are created as you work through the text and significant parts of a game engine are built and made available for download. The companion disc contains all of the resources described in the book, e.g. example code, game assets, video/sound editing software, and color figures. Instructor resources are available for use as a textbook.
- Lifetime access on eBooks with 352 pages
- Understand basic game development concepts using Python
- Learn about graphics, sound, artificial intelligence, animation & more
- Get a companion disc with example code, games assets & color figures
Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications. Later chapters cover the basics of searching, game playing, and knowledge representation. Expert systems and machine learning are covered in detail, followed by separate programming chapters on Prolog and Python. The concluding chapter on artificial intelligence machines and robotics is comprehensive with numerous modern applications.
- Lifetime access on eBooks with 203 pages
- Cover an introduction to concepts related to AI
- Learn about searching processes, knowledge representation, machine learning, expert systems, programming, & robotics
- Separate chapters on Prolog & Python to introduce basic programming techniques in AI
This book lends insight into solving some well-known AI problems using the most efficient methods by humans and computers. The book discusses the importance of developing critical-thinking methods and skills and develops a consistent approach toward each problem. This book covers some classic Ai problems such as Twelve Coins, Red Donkey, Cryptarithms, Rubik’s Cube, and more. It includes a playability site where you can exercise the process of developing their solutions.
- Lifetime access on eBooks with 300 pages
- Gain insights on solving well-known AI problems using efficient methods utilized by humans & computers
- Cover classic AI problems like Twelve Coins, Rubik’s Cube, Red Donkey & more
- Gain access to a playability site where you can exercise the process of developing AI solutions
- Describe problem-solving methods that can be applied to many problem situations
This book lends insight into solving some well-known AI problems using humans and computers’ most efficient problem-solving methods. The book discusses the importance of developing critical-thinking methods and skills and develops a consistent approach toward each problem. This book assembles in one place a set of interesting and challenging AI–type problems that students regularly encounter in computer science, mathematics, and AI courses. The book is instrumental as a companion to any course in computer science or mathematics where there are interesting problems to solve.
- Lifetime access on eBooks with 350 pages
- Address AI & problem-solving from different perspectives
- Cover classic AI problems such as Sudoku, Map Coloring, Twelve Coins, Red Donkey & more
- Get a companion disc with source code, solutions, figures & more
- Discover playability sites where students can exercise the process of developing their solutions
- Describe problem-solving methods that might be applied to a variety of situations
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to TensorFlow’s various “core” features, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks, after which you can do further reading to deepen your knowledge.
- Lifetime access on eBooks with 252 pages
- Introduction to the use of Python for code samples
- Discover TensorFlow 2 APIs & Datasets
- Get a comprehensive appendix that covers Keras & advanced topics such as NLPs, MLPs, RNNs, LSTMs
- Attain the companion files with all of the source code examples & figures (download from the publisher)
As part of the best-selling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of Python 3 to be able to work on their own projects. In addition to covering all of the basic concepts, the book features a chapter on PyGame, which allows a programmer to handle graphics, mouse and keyboard interaction, and play sounds and videos. Companion files that accompany this book contain all of the code examples as complete working programs. This means that there is no need to key them in to be executed and perhaps modified or expanded.
- Lifetime access on eBooks with 250 pages
- Know a chapter on PyGame which allows a programmer to handle graphics, mouse/keyboard interaction & play sounds and videos
- Explore communication in-depth, making use of one of Python’s best features
- Collect modules for sending & receiving email, communicating between computers, and working with Twitter and Web pages
- Know companion files that contain all of the code examples as complete working programs
- Know files that have all images from the text (including 4-color)
This book is designed to identify some of the current applications and techniques of artificial intelligence as an aid to solving problems and accomplishing tasks. It provides a general introduction to the various branches of AI, which include formal logic, reasoning, knowledge engineering, expert systems, neural networks, and fuzzy logic, etc. The book has been structured into five parts, emphasizing expert systems: problems and state-space search, knowledge engineering, neural networks, fuzzy logic, and Prolog.
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- Know the different branches of AI like formal logic, reasoning, knowledge engineering & more
- Get a separate chapter on Prolog to introduce basic programming techniques in AI
- Identify some AI applications & techniques
This text provides a comprehensive, colorful, up-to-date, and accessible presentation of AI without sacrificing theoretical foundations. It includes numerous examples, applications, full-color images, and human interest boxes to enhance student interest. Advanced topics cover neural nets, genetic algorithms, and complex board games. A companion DVD is included with resources, simulations, and figures from the book. Instructors’ resources are available upon adoption.
- Lifetime access on eBooks with 850 pages
- Get separate chapters on Robotics, Machine Learning & Computer Games
- Introduce important AI concepts like expert systems, use in video games, neural nets, machine learning & more through practical applications
- Gain DVD with resources, simulations & figures from the book
- Attain instructors’ resources such as solutions, Microsoft PP slides, and more that are available for adopters
This book introduces AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and autoencoders. Keras-based code samples are included to supplement the theoretical discussion. Besides, this book contains appendices for Keras, TensorFlow 2, and Pandas.
- Lifetime access on eBooks with 300 pages
- Cover an introduction to programming concepts related to AI, machine learning & deep learning
- Learn the material on Keras, TensorFlow2 & Pandas
- Gain insights on Artificial Intelligence & its relationship with other languages
This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2.
- Lifetime access on eBooks with 364 pages
- Achieve a basic understanding of Python 3 programming concepts related to machine learning
- Get separate appendices for regular expressions, Keras & TensorFlow2
- Get to know more about Numpy & Pandas and how they are related to Python 3 programming
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