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Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python
Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

The overall...

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

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...

Computational Statistics: An Introduction to R
Computational Statistics: An Introduction to R

Suitable for a compact course or self-study, Computational Statistics: An Introduction to R illustrates how to use the freely available R software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic knowledge of statistics and...

Practical DevOps
Practical DevOps

Key Features

  • Get to know the background of DevOps so you understand the collaboration between different aspects of an IT organization and a software developer
  • Improve your organization's performance to ensure smooth production of software and services
  • Deploy top-quality software and...
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Statistical Analysis of Financial Data in R (Springer Texts in Statistics)
Statistical Analysis of Financial Data in R (Springer Texts in Statistics)

Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can...

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Graphics in this book are printed in black and white.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data....

Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Learning DevOps: Continuously Deliver Better Software
Learning DevOps: Continuously Deliver Better Software

Learn to use some of the most exciting and powerful tools to deliver world-class quality software with continuous delivery and DevOps

About This Book

  • Get to know the background of DevOps so you understand the collaboration between different aspects of an IT organization and a software developer
  • ...
An Introduction to Analysis of Financial Data with R
An Introduction to Analysis of Financial Data with R

A complete set of statistical tools for beginning financial analysts from a leading authority

Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and...

Java: Data Science Made Easy
Java: Data Science Made Easy

Data collection, processing, analysis, and more

About This Book

  • Your entry ticket to the world of data science with the stability and power of Java
  • Explore, analyse, and visualize your data effectively using easy-to-follow examples
  • A highly practical course covering a broad...
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