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Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition

Build a strong foundation of machine learning algorithms in 7 days

Key Features

  • Use Python and its wide array of machine learning libraries to build predictive models
  • Learn the basics of the 7 most widely used machine learning algorithms within a week
  • Know...
Deployment of Microsoft Azure Cloud Solutions: A complete guide to cloud development using Microsoft Azure
Deployment of Microsoft Azure Cloud Solutions: A complete guide to cloud development using Microsoft Azure

Master all the important and tough decision-making aspects involved in architecting an Azure public cloud for your organization.

Key Features

  • Deploy Azure Active Directory and implement synchronization
  • Manage storage solutions with Azure network services
  • ...
Hands-On Artificial Intelligence with Java for Beginners: Build intelligent apps using machine learning and deep learning with Deeplearning4j
Hands-On Artificial Intelligence with Java for Beginners: Build intelligent apps using machine learning and deep learning with Deeplearning4j

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...
Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions
Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions

A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examples

Key Features

  • Designed to iteratively develop the skills of Python users who don't have a data science background
  • Covers the key foundational concepts...
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.

Key Features

  • Explore deep reinforcement learning (RL), from the first principles to the latest algorithms
  • Evaluate high-profile RL methods, including value...
Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python
Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python
Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement...
Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale
Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale

Build effective regression models in R to extract valuable insights from real data

Key Features

  • Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values
  • From Simple Linear Regression...
Mastering C++ Game Development: Create professional and realistic 3D games using C++ 17
Mastering C++ Game Development: Create professional and realistic 3D games using C++ 17

High-end game development with advanced C++ 17 programming techniques

Key Features

  • Make the best use of object-oriented capabilities of C++ to develop high-end games
  • Create reusable C++ libraries and editor tools for your game
  • Series of example projects...
Java 11 and 12 – New Features: Learn about Project Amber and the latest developments in the Java language and platform
Java 11 and 12 – New Features: Learn about Project Amber and the latest developments in the Java language and platform

Enhance your development skills with Java's state-of-the-art features and projects to make your applications leaner and faster

Key Features

  • Overcome the challenges involved in migrating to new versions of Java
  • Discover how Oracle has bridged the gap between Java and...
Program the Internet of Things with Swift for iOS: Learn How to Program Apps for the Internet of Things
Program the Internet of Things with Swift for iOS: Learn How to Program Apps for the Internet of Things

With this book, you will learn how to build apps and hardware for the Internet of Things, using Apple's native APIs and industry standard protocols like Bluetooth and HTTPS. You'll start out learning how to access the sensors on the iPhone, move on to building your own accessories using the Arduino and Raspberry
...
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

Dive deeper into neural networks and get your models trained, optimized with this quick reference guide

Key Features

  • A quick reference to all important deep learning concepts and their implementations
  • Essential tips, tricks, and hacks to train a variety of deep learning...
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