Python Machine Learning_ The Complete Guide to Understand Python Machine Learning for Beginners and Artificial Intelligence.pdf

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Python Machine Learning
The Complete Guide to Understand
Python Machine Learning for Beginners
and Artificial Intelligence
Table of Contents
Introduction
Chapter 1: Introduction (A Small History of Machine Learning)
History of Machine Learning
Key Machine Learning Terms and Their Definitions
Chapter 2: The Concept of Machine Learning
Definition and Application of Machine Learning
Key Elements of Machine Learning
Types of Artificial Intelligence Learning
Chapter 3: Mathematical Notation, Basic Terminology, and Building
Machine Learning Systems
Mathematical Notation for Machine Learning
Terminologies Used for Machine Learning
Road Map to Building Your Machine Learning Systems
Chapter 4: Using Python for Machine Learning
Variables
Application of Variables in Python
Essential Operator
Functions
Conditional Statements
Loop
Chapter 5: Artificial Neural Networks
Introduction to Artificial Neural Networks
Types of Artificial Neural Networks
Artificial Neural Network Layers
Advantages and Disadvantages of Neural Networks
Advantages of Artificial Neural Networks
Disadvantages of Artificial Neural Networks
Chapter 6: Machine Learning Classification
What Is Machine Learning Classification?
Types of Classifiers in Python Machine Learning
Machine learning classification models
Metrics for evaluating machine learning classification models
Chapter 7: Machine Learning Training Model
Simple Machine Training Model in Python
Simple ML Python Model using Linear Regression
Chapter 8: Developing a Machine Learning Model with Python
Installing the Python and SciPy Platforms
Loading the Dataset
Summarizing the Dataset
Visualizing the Dataset
Evaluating some Algorithms
Making some Predictions
Chapter 9: Training Simple Machine Learning Algorithms for
Classification
Linear Regression
Logistic Regression
Decision Tree
SVM
Naïve Bayes
KNN
K-Means Clustering
Random Forest
Dimensionality Reduction Algorithms
Gradient Boosting Algorithms
Chapter 10: Building Good Training Sets
How to Build the Data
Data Selection
Data Preprocessing
Data Conversion
Conclusion
Introduction
Congratulations on purchasing
Python Machine Learning: How to Learn
Machine Learning with Python, The Complete Guide to Understand Python
Machine Learning for Beginners and Artificial Intelligence,
and thank you
for doing so. The following chapters will discuss everything a beginner
would want to know about Machine learning, artificial intelligence, and
Python.
The first chapter is an introduction to Machine Learning and a history of
where it all began back in the 1940s to where it is at today. The chapter also
covers the terms popular in Machine learning and artificial intelligence
circles and their definitions. This is so that a beginner will understand the
language in the book without much struggle.
The second chapter is about the concept of machine learning. This chapter
offers an in-depth explanation of how machines gain the ability to think for
themselves the same way human beings do and the many ways people apply
machine learning in various fields. It continues to explain the key elements of
machine learning and gives a description of the types of Artificial
Intelligence learning available today.
The third chapter is about the mathematical notation for machine learning,
where the reader will understand the relationship between mathematical
nomenclatures and machine learning. The chapter also explains the
terminologies common in machine learning, and it concludes with a roadmap
for machine learning exploration.
The fourth chapter is an introduction to using Python for machine learning,
and it explains the basics an individual would need to understand about this
excellent coding language. The chapter explains the various stages involved
in machine learning using Python, and it contains real-life explanations of the
integral features and functions making up this language.
The fifth chapter is an explanation of Artificial Neural Networks in machine
learning. This chapter goes into detail to show how the human brain is the
main inspiration for machine learning and how with time machines will have
the ability to reason the same way human beings do. The chapter explains the
meaning of neural networks, the classifiers in Python machine learning, the
machine learning models, and the metrics for evaluating machine-learning
models.

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