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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...

Artificial Intelligence: A New Synthesis (The Morgan Kaufmann Series in Artificial Intelligence)
Artificial Intelligence: A New Synthesis (The Morgan Kaufmann Series in Artificial Intelligence)

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and...

The Top Ten Algorithms in Data Mining
The Top Ten Algorithms in Data Mining

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a...

Learning scikit-learn: Machine Learning in Python
Learning scikit-learn: Machine Learning in Python

Incorporating machine learning in your applications is becoming essential. As a programmer this book is the ideal introduction to scikit-learn for your Python environment, taking your skills to a whole new level.

Overview

  • Use Python and scikit-learn to create intelligent applications
  • Apply...
Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)
Bayesian Brain: Probabilistic Approaches to Neural Coding (Computational Neuroscience)

A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering...

Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

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...
Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings
Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings
This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004.

The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning,...

Mastering Probabilistic Graphical Models using Python
Mastering Probabilistic Graphical Models using Python

Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python

About This Book

  • Gain in-depth knowledge of Probabilistic Graphical Models
  • Model time-series problems using Dynamic Bayesian Networks
  • A practical guide to...
Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications
Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications
A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques

This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips...

The Avid Handbook: Advanced Techniques, Strategies, and Survival Information for Avid Editing Systems, 5th Edition
The Avid Handbook: Advanced Techniques, Strategies, and Survival Information for Avid Editing Systems, 5th Edition
"The Avid Handbook has always been an useful supplement to Avid's own excellent manuals. Greg Staten's latest edition introduces readers to the inner workings, tips, tricks and hidden techniques behind Avid's newly updated Media Composer 3.0 software. Avid's manuals can teach you the right buttons to push, but Staten takes you further into the...
Machine Learning in Action
Machine Learning in Action

After college I went to work for Intel in California and mainland China. Originally my plan was to go back to grad school after two years, but time flies when you are having fun, and two years turned into six. I realized I had to go back at that point, and I didn’t want to do night school or online learning, I wanted to sit on...

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