Publisher's Synopsis
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!
