IT eBooks
Download, Read, Use
TensorFlow 2.x in the Colaboratory Cloud
TensorFlow 2.x in the Colaboratory Cloud

Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow 2.x along with Colab's easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else - Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks - is provided and ready to go from Colab. The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and testing. You will fi ...
Learning Perl, 8th Edition
Learning Perl, 8th Edition

If you're just getting started with Perl, this is the book you want—whether you're a programmer, system administrator, or web hacker. Nicknamed "the Llama" by two generations of users, this best seller closely follows the popular introductory Perl course taught by the authors since 1991. This eighth edition covers recent changes to the language up to version 5.34. Perl is suitable for almost any task on almost any platform, from short fixes to complete web applications. Learning Perl teaches you the basics and shows you how to write simple, single-file programs—roughly 90% of the Perl programs in use today. And each chapter includes exercises to help you practice what you've just learned. Other books may teach you to program in Perl, but this book will turn you into a Perl programmer. Topics include: Perl data and variable types; Subroutines; File operations; Regular expressions; String manipulation (including Unicode); Lists and sorting; Process management; Use of third-part ...
Learning ZeroMQ
Learning ZeroMQ

Even connecting a few programs across a few sockets is plain nasty when you start to handle real life situations. Trillions? The cost would be unimaginable. Connecting computers is so difficult that software and services to do this is a multi-billion dollar business. So today we're still connecting applications using raw UDP and TCP, proprietary protocols, HTTP, Websockets. It remains painful, slow, hard to scale, and essentially centralized. To fix the world, we needed to do two things. One, to solve the general problem of "how to connect any code to any code, anywhere". Two, to wrap that up in the simplest possible building blocks that people could understand and use easily. It sounds ridiculously simple. And maybe it is. That's kind of the whole point. If you are a programmer and you aim to build large systems, in any language, then Code Connected is essential reading. Code Connected Volume 1 takes you through learning ZeroMQ, step-by-step, with over 80 examples. You will learn t ...
Deep Learning Patterns and Practices
Deep Learning Patterns and Practices

The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch's work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You'll build your skills and confidence with each interesting example. Deep Learning Patterns and Practices is a deep dive into building successful deep ...
Learning Test-Driven Development
Learning Test-Driven Development

Your code is a testament to your skills as a developer. No matter what language you use, code should be clean, elegant, and uncluttered. By using test-driven development (TDD), you'll write code that's easy to understand, retains its elegance, and works for months, even years, to come. With this indispensable guide, you'll learn how to use TDD with three different languages: Go, JavaScript, and Python. Author Saleem Siddiqui shows you how to tackle domain complexity using a unit test-driven approach. TDD partitions requirements into small, implementable features, enabling you to solve problems irrespective of the languages and frameworks you use. With Learning Test-Driven Development at your side, you'll learn how to incorporate TDD into your regular coding practice. This book helps you: Use TDD's divide-and-conquer approach to tame domain complexity; Understand how TDD works across languages, testing frameworks, and domain concepts; Learn how TDD enables continuous integration; ...
Math for Deep Learning
Math for Deep Learning

Deep learning is everywhere, making this powerful driver of AI something more STEM professionals need to know. Learning which library commands to use is one thing, but to truly understand the discipline, you need to grasp the mathematical concepts that make it tick. This book will give you a working knowledge of topics in probability, statistics, linear algebra, and differential calculus - the essential math needed to make deep learning comprehensible, which is key to practicing it successfully. Each of the four subfields are contextualized with Python code and hands-on, real-world examples that bridge the gap between pure mathematics and its applications in deep learning. Chapters build upon one another, with foundational topics such as Bayes' theorem followed by more advanced concepts, like training neural networks using vectors, matrices, and derivatives of functions. You'll ultimately put all this math to use as you explore and implement deep learning algorithms, including backp ...
How to Think Like a Computer Scientist
How to Think Like a Computer Scientist

How to Think Like a Computer Scientist: Learning with Python - is an introduction to computer science using the Python programming language. It covers the basics of computer programming, including variables and values, functions, conditionals and control flow, program development and debugging. Later chapters cover basic algorithms and data structures. ...
Learning Go
Learning Go

This is an introduction to the Go language from Google. Its aim is to provide a guide to this new and innovative language. The intended audience of this book is people who are familiar with programming and know multiple programming languages,be it C, C++, Perl, Java, Erlang, Scala or Haskell. This is not a book which teaches you how to program, this is a bookthat just teaches you how to use Go. As with learning new things, probably the best way to do this is to discover it for yourself by creating your own programs. Therefor includes each chapter a number of exercises (and answers) to acquaint you with the language. ...
Transformers for Natural Language Processing, 2nd Edition
Transformers for Natural Language Processing, 2nd Edition

Transformers are a game-changer for natural language understanding (NLU) and have become one of the pillars of artificial intelligence. Transformers for Natural Language Processing, 2nd Edition, investigates deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question-answering, and many more NLP domains with transformers. An Industry 4.0 AI specialist needs to be adaptable; knowing just one NLP platform is not enough anymore. Different platforms have different benefits depending on the application, whether it's cost, flexibility, ease of implementation, results, or performance. In this book, we analyze numerous use cases with Hugging Face, Google Trax, OpenAI, and AllenNLP. This book takes transformers' capabilities further by combining multiple NLP techniques, such as sentiment analysis, named entity recognition, and semantic role labeling, to analyze complex use cases, such as dissecting fake news on Twitter. Also, see how transformers ...
Learning TypeScript
Learning TypeScript

TypeScript has conquered the world of JavaScript: it's one of the world's fastest growing and most popular languages across developer surveys, widely used in consumer and business companies alike, and frequently credited for helping massive web applications scale. But what is TypeScript? How does it work, why does it work, and how can we use it? Learning TypeScript takes beginner to intermediate JavaScript programmers from knowing nothing about "types" or a "type system" to full mastery of the fundamentals of TypeScript. It's more than a means to find bugs and typos - it's a useful system for declaring the way our JavaScript should work and helping us stick to it. You'll learn how TypeScript: interacts with JavaScript; analyzes and understands code; augments your existing development pattern; helps you document your code; works with IDEs to provide refactoring tools; assists local development in refactoring code; helps you develop more quickly with fewer bugs. ...
← Prev       Next →
Reproduction of site books is authorized only for informative purposes and strictly for personal, private use.
Only Direct Download
IT eBooks Group © 2011-2025