Machine Learning For Absolute Beginners

By: Oliver Theobald

Ready to spin up a virtual GPU instance and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile?

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Book Description

Ready to spin up a virtual GPU instance and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile?

Well, hold on there...

Before you embark on your epic journey, there are some high-level theory and statistical principles to weave through first.

But rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this book provides a practical and high-level introduction to machine learning.

Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home.


In This Step-By-Step Guide You Will Learn:

• How to download free datasets
• What tools and machine learning libraries you need
• Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data
• Preparing data for analysis, including k-fold Validation
• Regression analysis to create trend lines
• Clustering, including k-means clustering, to find new relationships
• The basics of Neural Networks
• Bias/Variance to improve your machine learning model
• Decision Trees to decode classification
• How to build your first Machine Learning Model to predict house values using Python

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