What You Need to Know about Machine Learning

By Gabriel A. Canepa

This eBook offers you the perfect place to lay the foundation for your work in the world of Machine Learning, providing the basic understanding, knowledge, and skills that you can build on with experience and time.

What you will learn:

Discover the various forms Machine Learning, and take that which will benefit you the most

Pick up the Python tools you need to know: from pandas to scikit-learn

Learn the relationship between machine learning and big data

Understand and identify potential real-world scenarios where machine learning can be applied

Lay the foundations to get started in the wide world of machine learning

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HTML5 Graphing and Data Visualization Cookbook

By Ben Fhala

Get a complete grounding in the exciting visual world of Canvas and HTML5 using this recipe-packed cookbook. Learn to create charts and graphs, draw complex shapes, add interactivity, work with Google maps, and much more.

What you will learn:

Creating graphics in Canvas 2D and draw complex shapes

Building most of the common charts through step-by-step recipes

Adding interactivity to canvas elements and create your own JavaScript animation engine

Discovering many fantastic charting solutions and learn how to deal with their capabilities and how to change them as well

Learning how to work with Google maps , Google Charts, and Google Docs API

Integrating your data into live data, xml driven data, objects, and strings

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Building Machine Learning Systems with Python

By Willi Richert, Luis Pedro Coelho

Expand your knowledge of Python data with the power of machine learning with this eBook. Find out how to use cutting-edge Python machine learning algorithms to reveal the hidden insight in your data. You'll learn how to build machine learning for text, images, and sounds with free open-source tools and libraries.

What you will learn:

Build a classification system that can be applied to text, images, or sounds

Use Numpy, ScipY, scikit-learn, and Matplotlib: Python open-source libraries for data and machine learning

Employ Amazon Web Services to run analyses on the cloud

Recommend products to users based on past purchases

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Practical Data Analysis

By Hector Cuesta

This eBook is designed to give you the knowledge you need to start succeeding in data analysis. Discover the tools, techniques and algorithms you need to transform your data into insight.

What you will learn:

Work with data to get meaningful results from your data analysis projects

Visualize your data to find trends and correlations

Build your own image similarity search engine

Learn how to forecast numerical values from time series data

Create an interactive visualization for your social media graph

Explore the MapReduce framework in MongoDB

Create interactive simulations with D3js

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Machine Learning with R

By Brett Lantz

Tech consultants and BI experts will charge a lot to help you turn data into actionable insights. This eBook will help you do just that - without costing a thing. Your business can't afford to waste its data - and you shouldn't waste this opportunity to kickstart your skillset.

What you will learn:

Get to grips with the basics of machine learning

Find out how to classify data using nearest neighbor methods

Learn Bayesian methods to classify data

Predict values using decision trees, rules, and support vector machines

Model data using neural networks

Join a global community of statisticians and data scientists putting R to work to produce stunning insights

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