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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