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Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications....
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn

Key Features

  • Build a variety of Hidden Markov Models (HMM)
  • Create and apply models to any sequence of data to analyze, predict, and extract valuable...
Beginning Robotics with Raspberry Pi and Arduino: Using Python and OpenCV
Beginning Robotics with Raspberry Pi and Arduino: Using Python and OpenCV

Learn how to use a Raspberry Pi in conjunction with an Arduino to build a basic robot with advanced capabilities. Getting started in robotics does not have to be difficult. This book is an insightful and rewarding introduction to robotics and a catalyst for further directed study. 

You'll be led step by step...

Practical Machine Learning
Practical Machine Learning

About This Book

  • Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark
  • Comprehensive practical solutions taking you into the future of machine learning
  • Go a step further and integrate your machine learning projects with...
Python Pocket Reference
Python Pocket Reference
This is the book to reach for when you're coding on the fly and need an answer now. It's an easy-to-use reference to the core language, with descriptions of commonly used modules and toolkits, and a guide to recent changes, new features, and upgraded built-ins -- all updated to cover Python 3.x as well as version 2.6. You'll also quickly find...
Text Processing in Python
Text Processing in Python

Text Processing in Python is an example-driven, hands-on tutorial that carefully teaches programmers how to accomplish numerous text processing tasks using the Python language. Filled with concrete examples, this book provides efficient and effective solutions to specific text processing problems and practical...

Python: Data Analytics and Visualization
Python: Data Analytics and Visualization

Understand, evaluate, and visualize data About This Book - Learn basic steps of data analysis and how to use Python and its packages - A step-by-step guide to predictive modeling including tips, tricks, and best practices - Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for...

Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python

Key Features

  • Enter the world of artificial intelligence using the power of Python
  • An example-rich guide to master various RL and DRL algorithms
  • Explore...
Python Pocket Reference (Pocket Reference)
Python Pocket Reference (Pocket Reference)

Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. You’ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy...

TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0
TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks.

Key Features

  • Train your own models for effective prediction, using high-level Keras API
  • Perform supervised and unsupervised machine learning and learn...
Practical Data Science Cookbook - Real-World Data Science Projects to Help You Get Your Hands On Your Data
Practical Data Science Cookbook - Real-World Data Science Projects to Help You Get Your Hands On Your Data

Key Features

  • Learn how to tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize data
  • Get beyond the theory with real-world projects
  • Expand your numerical programming skills through step-by-step code examples and learn more about the robust...
Learning Data Mining with Python
Learning Data Mining with Python

Harness the power of Python to analyze data and create insightful predictive models

About This Book

  • Learn data mining in practical terms, using a wide variety of libraries and techniques
  • Learn how to find, manipulate, and analyze data using Python
  • Step-by-step instructions...
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