Python Machine Learning: Step-by-Step Guide for Beginners to Unlock the Power of Machine Learning and Artificial Neural Networks using Python Programming

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Python Machine Learning: Step-by-Step Guide for Beginners to Unlock the Power of Machine Learning and Artificial Neural Networks using Python Programming

Freeman Booker

ISBN10: 1713083566

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Python Machine Learning: Step-by-Step Guide for Beginners to Unlock the Power of Machine Learning and Artificial Neural Networks using Python Programming

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Take your basic understanding of Python to the next level!
Machine learning has been a truly game-changing force in the tech world. These days deep learning is driving that even further!
Need to understand this challenging new world quickly?
Complete 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.
Here is a preview of what you will learn in this guide:
  • “Pandas” Python Library
  • Data Scrubbing
  • NumPy:
  • Dropping Unnecessary Columns in a Data Frame
  • Changing 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 Harnes

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title Python Machine Learning
subtitle Step-by-Step Guide for Beginners to Unlock the Power of Machine Learning and Artificial Neural Networks Using Python Programming
authors Freeman Booker
publishedDate 2019-11-29
description Take your basic understanding of Python to the next level!Machine learning has been a truly game-changing force in the tech world. These days deep learning is driving that even further! Need to understand this challenging new world quickly?Complete 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.Here is a preview of what you will learn in this guide: "Pandas" Python Library Data Scrubbing NumPy: Dropping Unnecessary Columns in a Data Frame Changing 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! Even if you have only a very basic understanding of Python with no machine learning experience, have no fear! With this guide in your hands that will not be a barrier for you any longer. Understand Machine Learning in Python quickly and easily when you grab this guide now!
pageCount 108
printType BOOK
maturityRating NOT_MATURE
panelizationSummary
language en
canonicalVolumeLink https://books.google.com/books/about/Python_Machine_Learning.html?hl=&id=PSkhzAEACAAJ

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