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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...
Using Docker: Developing and Deploying Software with Containers
Using Docker: Developing and Deploying Software with Containers

Docker containers offer simpler, faster, and more robust methods for developing, distributing, and running software than previously available. With this hands-on guide, you’ll learn why containers are so important, what you’ll gain by adopting Docker, and how to make it part of your development...

Microservices: Flexible Software Architecture
Microservices: Flexible Software Architecture

The Most Complete, Practical, and Actionable Guide to Microservices

 

Going beyond mere theory and marketing hype, Eberhard Wolff presents all the knowledge you need to capture the full benefits of this emerging paradigm. He illuminates...

Data Structures: Abstraction and Design Using Java, 3rd edition
Data Structures: Abstraction and Design Using Java, 3rd edition
Our goal in writing this book was to combine a strong emphasis on problem solving and software design with the study of data structures. To this end, we discuss applications of each data structure to motivate its study. After providing the specification (interface) and the implementation (a Java class), we then cover case studies...
Mastering Concurrency Programming with Java 8
Mastering Concurrency Programming with Java 8

Master the principles and techniques of multithreaded programming with the Java 8 Concurrency API

About This Book

  • Implement concurrent applications using the Java 8 Concurrency API and its new components
  • Improve the performance of your applications or process more data at the same time,...
Introduction to Machine Learning with Python: A Guide for Data Scientists
Introduction to Machine Learning with Python: A Guide for Data Scientists

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available...

Docker in Practice
Docker in Practice

Summary

An open source container system, Docker makes deploying applications painless and flexible. Docker is powerful and simple to use, and it makes life easier for developers and administrators alike providing shorter build times, fewer production bugs, and effortless application roll-out.

About...

Data Science and Complex Networks: Real Case Studies with Python
Data Science and Complex Networks: Real Case Studies with Python

This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web...

TypeScript Design Patterns
TypeScript Design Patterns

Key Features

  • This step-by-step guide will would demonstrate all the important design patterns in practice
  • This book is the only documentation on the market focusing on design patterns in TypeScript
  • This book is packed with rich examples that will improve...
Java in 21 Days, Sams Teach Yourself (Covering Java 8) (7th Edition)
Java in 21 Days, Sams Teach Yourself (Covering Java 8) (7th Edition)

In just 21 days you can acquire the knowledge and skills necessary to develop applications on your computer and apps that run on Android phones and tablets. With this complete tutorial you’ll quickly master the basics and then move on to more advanced features and concepts.

Completely updated for Java 8,...

Python Machine Learning Cookbook
Python Machine Learning Cookbook

100 recipes that teach you how to perform various machine learning tasks in the real world

About This Book

  • Understand which algorithms to use in a given context with the help of this exciting recipe-based guide
  • Learn about perceptrons and see how they are used to build neural...
R Deep Learning Essentials
R Deep Learning Essentials

Key Features

  • Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
  • Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
  • Build models relating to neural...
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