Machine Learning with Python : Unlocking AI Potential with Python and Machine Learning / Oliver Theobald.

Format:

Book

Author/Creator:

Theobald, Oliver, author.

Language:

English

Subjects (All):

Machine learning.

Python (Computer program language).

Data mining.

Physical Description:

1 online resource (146 pages)

Edition:

First edition.

Place of Publication:

Birmingham, England : Packt Publishing, Limited, [2024]

Biography/History:

Theobald Oliver: Oliver Theobald, a technical writer and best-selling author, excels in AI, fintech, and cloud computing. With global experience, he now resides between China and Japan, deepening his expertise in technology. As an instructor, Oliver emphasizes clarity and engagement, stripping away jargon to make complex topics accessible. His courses aim to empower both beginners and professionals with practical skills for success in the tech industry, making learning both effective and enjoyable.

Summary:

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.

Contents:

Intro

FOREWORD

DATASETS USED IN THIS BOOK

INTRODUCTION

DEVELOPMENT ENVIRONMENT

MACHINE LEARNING LIBRARIES

EXPLORATORY DATA ANALYSIS

DATA SCRUBBING

PRE-MODEL ALGORITHMS

SPLIT VALIDATION

LOGISTIC REGRESSION

SUPPORT VECTOR MACHINES

k-NEAREST NEIGHBORS

TREE-BASED METHODS

NEXT STEPS

APPENDIX 1: INTRODUCTION TO PYTHON

APPENDIX 2: PRINT COLUMNS

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Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9781835462072

1835462073

OCLC:

1425945928