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Python Machine Learning by Leonard Lee ebook deal
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Python Machine Learning

By: Leonard Lee

Want to get up to speed fast?
Completely up to date, this guide to Python Machine Learning includes a detailed treatment of the popular TensorFlow deep learning library, scikit-learn, and much more. By reading this book, you will be better prepared to meet the challenges and opportunities of data analysis that exist in the world today, and tomorrow.

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Book Description

Want to get up to speed fast?
Completely up to date, this guide to Python Machine Learning includes a detailed treatment of the popular TensorFlow deep learning library, scikit-learn, and much more. By reading this book, you will be better prepared to meet the challenges and opportunities of data analysis that exist in the world today, and tomorrow.

Here is a preview of what you will learn in this guide:

-What is Machine Learning?
-Machine Learning Tasks
-Supervised vs. Unsupervised Learning
-Machine Learning Applications
-Classification
-Clustering
-Density Estimation
-Dimensionality Reduction
-Regression Analysis
-Machine Learning in Python
-Scikit - learn
-TensorFlow
-What Version of Python to Use?
-Installing the relevant libraries (If not using Anaconda)
-Introductory Machine Learning in Python: Iris Flowers
-Importing the Requisite Libraries and data
-Summarizing the Data Set
-Data Visualization
-Creating Data Models
-Making Predictions
-Common Data Models Used in Machine Learning
-Simple Linear Algorithms
-Nonlinear Algorithms
-What is a Neural Network?
-Sample Neural Network Code
And so much more!

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