Book Image

Machine Learning with Python

By : Oliver Theobald
Book Image

Machine Learning with Python

By: Oliver Theobald

Overview of this book

The course starts by setting the foundation with an introduction to machine learning, Python, and essential libraries, ensuring you grasp the basics before diving deeper. It then progresses through exploratory data analysis, data scrubbing, and pre-model algorithms, equipping you with the skills to understand and prepare your data for modeling. The journey continues with detailed walkthroughs on creating, evaluating, and optimizing machine learning models, covering key algorithms such as linear and logistic regression, support vector machines, k-nearest neighbors, and tree-based methods. Each section is designed to build upon the previous, reinforcing learning and application of concepts. Wrapping up, the course introduces the next steps, including an introduction to Python for newcomers, ensuring a comprehensive understanding of machine learning applications.

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Table of Contents (18 chapters)
Free Chapter
1
FOREWORD
FOREWORD
2
DATASETS USED IN THIS BOOK
DATASETS USED IN THIS BOOK
3
INTRODUCTION
INTRODUCTION
4
DEVELOPMENT ENVIRONMENT
DEVELOPMENT ENVIRONMENT
5
MACHINE LEARNING LIBRARIES
MACHINE LEARNING LIBRARIES
6
EXPLORATORY DATA ANALYSIS
EXPLORATORY DATA ANALYSIS
7
DATA SCRUBBING
DATA SCRUBBING
8
PRE-MODEL ALGORITHMS
PRE-MODEL ALGORITHMS
9
SPLIT VALIDATION
SPLIT VALIDATION
10
MODEL DESIGN
MODEL DESIGN
11
LINEAR REGRESSION
LINEAR REGRESSION
12
LOGISTIC REGRESSION
LOGISTIC REGRESSION
13
SUPPORT VECTOR MACHINES
SUPPORT VECTOR MACHINES
14
k-NEAREST NEIGHBORS
k-NEAREST NEIGHBORS
15
TREE-BASED METHODS
TREE-BASED METHODS
16
NEXT STEPS
NEXT STEPS
APPENDIX 1: INTRODUCTION TO PYTHON
APPENDIX 1: INTRODUCTION TO PYTHON
APPENDIX 2: PRINT COLUMNS
APPENDIX 2: PRINT COLUMNS

APPENDIX 1: INTRODUCTION TO PYTHON

 

Python was designed by Guido van Rossum at the National Research Institute for Mathematics and Computer Science in the Netherlands during the late 1980s and early 1990s. Derived from the Unix shell command-line interpreter and other programming languages including C and C++, it was designed to empower developers to write programs with fewer lines of code than other languages.21 Unlike other programming languages, Python also incorporates many English keywords where other languages use punctuation symbols.

In Python, the input code is read by the Python interpreter to perform an output. Any errors, including poor formatting, misspelled functions, or random characters left someplace in your script are picked up by the Python interpreter and cause a syntax error.

In this chapter we will discuss the basic syntax to help you write fluid and effective code.

 

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