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Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems
Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner....

Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras

Explore various Generative Adversarial Network architectures using the Python ecosystem

Key Features

  • Use different datasets to build advanced projects in the Generative Adversarial Network domain
  • Implement projects ranging from generating 3D shapes to a face aging...
Learning IPython for Interactive Computing and Data Visualization
Learning IPython for Interactive Computing and Data Visualization

IPython provides a rich architecture for interactive computing, and as a Python developer you can take advantage of this practical hands-on guide to make yourself an expert. Covers numerical computing, data analysis, and more.

Overview

  • A practical step-by-step tutorial which will help you to replace the...
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents

A practical guide to mastering reinforcement learning algorithms using Keras

Key Features

  • Build projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into action
  • Get to grips with Keras and practice on real-world unstructured...
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...
Practical Computer Vision: Extract insightful information from images using TensorFlow, Keras, and OpenCV
Practical Computer Vision: Extract insightful information from images using TensorFlow, Keras, and OpenCV

A practical guide designed to get you from basics to current state of art in computer vision systems.

Key Features

  • Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease
  • Leverage the power of Python,...
Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples
Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples
Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as...
Bluetooth Essentials for Programmers
Bluetooth Essentials for Programmers
This book provides an introduction to Bluetooth programming, with a specific focus on developing real code. The authors discuss the major concepts and techniques involved in Bluetooth programming, with special emphasis on how they relate to other networking technologies. They provide specific descriptions and examples for creating applications in...
PySpark Recipes: A Problem-Solution Approach with PySpark2
PySpark Recipes: A Problem-Solution Approach with PySpark2
Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved!

Data Science from Scratch: First Principles with Python
Data Science from Scratch: First Principles with Python

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from...

Deep Learning for Natural Language Processing: Creating Neural Networks with Python
Deep Learning for Natural Language Processing: Creating Neural Networks with Python
Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.

You’ll start by covering the mathematical prerequisites...
Rust Essentials
Rust Essentials

Discover how to use Rust to write fast, secure, and concurrent systems and applications

About This Book

  • Learn how to create secure and blazingly fast programs in Rust
  • Start working with Rust in a multicore and distributed environment
  • Explore the core characteristics of Rust...
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