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Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

About This Book

  • A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices
  • Get to grips with the basics of Predictive...
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...

Microservices Deployment Cookbook
Microservices Deployment Cookbook

Key Features

  • Adopt microservices-based architecture and deploy it at scale
  • Build your complete microservice architecture using different recipes for different solutions
  • Identify specific tools for specific scenarios and deliver immediate business results, correlate use cases, and adopt them...
DevOps with Kubernetes: Accelerating software delivery with container orchestrators
DevOps with Kubernetes: Accelerating software delivery with container orchestrators

Learn to implement DevOps using Docker & Kubernetes.

About This Book

  • Learning DevOps, container, and Kubernetes within one book.
  • Leverage Kubernetes as a platform to deploy, scale, and run containers efficiently.
  • A practical guide towards container management and...
Data Mining and Business Analytics with R
Data Mining and Business Analytics with R

Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are...

Mastering Machine Learning With scikit-learn
Mastering Machine Learning With scikit-learn

Apply effective learning algorithms to real-world problems using scikit-learn

About This Book

  • Design and troubleshoot machine learning systems for common tasks including regression, classification, and clustering
  • Acquaint yourself with popular machine learning algorithms, including...
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...
Building Machine Learning Systems with Python
Building Machine Learning Systems with Python

As the Big Data explosion continues at an almost incomprehensible rate, being able to understand and process it becomes even more challenging. With Building Machine Learning Systems with Python, you'll learn everything you need to tackle the modern data deluge - by harnessing the unique capabilities of Python and its extensive range of...

Computational Intelligence in Biomedical Engineering
Computational Intelligence in Biomedical Engineering

As in many other fields, biomedical engineers benefit from the use of computational intelligence (CI) tools to solve complex and non-linear problems. The benefits could be even greater if there were scientific literature that specifically focused on the biomedical applications of computational intelligence techniques. The first comprehensive...

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...

Principles of Data Mining (Undergraduate Topics in Computer Science)
Principles of Data Mining (Undergraduate Topics in Computer Science)

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each...

Mining of Massive Datasets
Mining of Massive Datasets
This book evolved from material developed over several years by Anand Rajaraman and Jeff Ullman for a one-quarter course at Stanford. The course CS345A, titled “Web Mining,” was designed as an advanced graduate course, although it has become accessible and interesting to advanced undergraduates.

The popularity of...

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