Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks
Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks
Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples.

Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian
...
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...
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...

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...
The Variational Bayes Method in Signal Processing
The Variational Bayes Method in Signal Processing
This is the first book-length treatment of the Variational Bayes (VB) approximation in signal processing. It has been written as a self-contained, self-learning guide for academic and industrial research groups in signal processing, data analysis, machine learning, identification and control. It reviews the VB distributional approximation, showing...
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...

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...

Building Probabilistic Graphical Models with Python
Building Probabilistic Graphical Models with Python

Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications

About This Book

  • Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image...
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...

Machine Learning with R - Second Edition
Machine Learning with R - Second Edition

Key Features

  • Harness the power of R for statistical computing and data science
  • Explore, forecast, and classify data with R
  • Use R to apply common machine learning algorithms to real-world scenarios

Book Description

Machine learning, at its core, is concerned...

Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Understand, explore, and effectively present data using the powerful data visualization techniques of Python

Key Features

  • Use the power of Pandas and Matplotlib to easily solve data mining issues
  • Understand the basics of statistics to build powerful predictive data...
Result Page: 3 2 1 
©2019 LearnIT (support@pdfchm.net) - Privacy Policy