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TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

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Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines.

TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms.

  • Learn TensorFlow fundamentals, including how to perform basic computation
  • Build simple learning systems to understand their mathematical foundations
  • Dive into fully connected deep networks used in thousands of applications
  • Turn prototypes into high-quality models with hyperparameter optimization
  • Process images with convolutional neural networks
  • Handle natural language datasets with recurrent neural networks
  • Use reinforcement learning to solve games such as tic-tac-toe
  • Train deep networks with hardware including GPUs and tensor processing units
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Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...

Learn Bitcoin and Blockchain: Understanding blockchain and Bitcoin architecture to build decentralized applications
Learn Bitcoin and Blockchain: Understanding blockchain and Bitcoin architecture to build decentralized applications

Get up and running with the fundamentals of Bitcoin and blockchain

Key Features

  • Learn quick, effective, and easy ways to master blockchain and Bitcoin
  • Understand the impact of decentralization and discover ways to tackle it
  • Explore the future of Bitcoin...
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...


Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python

Automate data and model pipelines for faster machine learning applications

Key Features

  • Build automated modules for different machine learning components
  • Understand each component of a machine learning pipeline in depth
  • Learn to use different open source...
Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Programming Fundamentals: A Modular Structured Approach Using C++
Programming Fundamentals: A Modular Structured Approach Using C++
The approach of this text is to take learners through a progression of materials in order to develop skills of modular, structured programming. The text was written, for the most part, without consideration of a specific programming language. However, in many cases the C++ language is discussed as part of the explanation of the concept. Often...
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