English | 2019 | ISBN: 1713083566 | 75 pages | EPUB,PDF,AZW3 | 1.2 Mb

Take your basic understanding of Python to the next level!

Machine learning has been a truly game-chag force in the tech world. These days deep learning is driving that even further!

Need to understand this challeg new world quicklyComplete and up to date for 2020, Python Machine Learning contains a comprehensive explanation of the key points you need to know including data scrubbing, regression analysis, decision trees, and artificial neural networks as well as a deep dive into building a model that works. By reading this book, you will be better prepared to meet tomorrow's challenges using cutting edge technology.

"Pandas" Python Library

Data Scrubbing

NumPy:

Dropping Unnecessary Columns in a Data Frame

Chag the Index of a Data Frame

Tidying up Data Fields

How to Combine str methods with NumPy when Cleaning Column

Cleaning the Whole Data set by making use of the applymap Function

Renaming Columns and Skipping Rows

Setting Up Data

Iris flowers data set

Importing the Requisite Libraries and data

Summarizing the Data Set

Defining Data Set Dimensions

List Data Type

Examining our Data

Creating a Statistical Summary

Examining the Class Distribution of the Given Data Set

Regression Analysis

Linear Regression

Linear Discriminant Analysis

Nonlinear Algorithms

Support Vector Machine (Clustering Methods)

Gaussian Naïve Bayes

K - Nearest Neighbors (Clustering and Bias/ Weighting Methods)

Artificial Neural Networks

What's the difference between Neural Networks and Conventional Computers

Sample Neural Network Code

Building a Model

Creating a Validation Data Set

Creating a Test Harness

Pseudo - random Number Generators

Making Predictions

And so much more!



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