Daniel Nedal - Introduction to Machine Learning with Python: A Guide for Beginners in Data Science

INTRODUCTION TO MACHINE LEARNING WITH PYTHON

A Guide for Beginners in Data Science

Daniel Nedal & Peters Morgan

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Table of Contents

Copyright 2018 by AI Sciences

All rights reserved.

First Printing, 2018

Edited by Davies Company

Ebook Converted and Cover by Pixels Studio

Publised by AI Sciences LLC

ISBN-13: 978-1724417503

ISBN-10: 1724417509

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Please note the information contained within this document is for educational and entertainment purposes only. No warranties of any kind are expressed or implied. Readers acknowledge that the author is not engaging in the rendering of legal, financial, medical or professional advice. Please consult a licensed professional before attempting any techniques outlined in this book.

By reading this document, the reader agrees that under no circumstances is the author responsible for any losses, direct or indirect, which are incurred as a result of the use of information contained within this document, including, but not limited to, errors, omissions, or inaccuracies.

To all the Data Scientist and Computer Scientist in the World

Authors Biography

Daniel Nedal is a data scientist and long-time user of the Python. He currently works as a computer scientist and as a research director at one of the biggest University in Paris.

Peters Morgan is a lecturer at the Data Science Institute at Melbourne University and a long-time user and developer of the Python. He is one of the core developers of some data science libraries in Python. Peter worked also as Machine Learning Scientist at Google for many years.

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Preface

Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence.

Ginni Rometty

The main purpose of this book is to provide the reader with the most fundamental knowledge of machine learning with Python so that they can understand what these are all about.

Book Objectives

This book will help you:

• Have an appreciation for machine learning and deep learning and an understanding of their fundamental principles.
• Have an elementary grasp of machine learning concepts and algorithms.
• Have achieved a technical background in machine learning and also deep learning

Target Users

The book designed for a variety of target audiences. The most suitable users would include:

• Newbies in computer science techniques and machine learning
• Professionals in machine learning and social sciences
• Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way
• Students and academicians, especially those focusing on machine learning practical guide using R

Is this book for me?

If you want to smash machine learning from scratch, this book is for you. Little programming experience is required. If you already wrote a few lines of code and recognize basic programming statements, youll be OK.

Why this book?

This book is written to help you learn machine learning using Python programming. If you are an absolute beginner in this field, youll find that this book explains complex concepts in an easy to understand manner without math or complicated theorical elements. If you are an experienced data scientist, this book gives you a good base from which to explore machine learning application.

Topics are carefully selected to give you a broad exposure to machine learning application. While not overwhelming you with information overload.

The example and cases studies are carefully chosen to demonstrate each algorithm and model so that you can gain a deeper understand of machine learning. Inside the book and in the appendices at the end of the book we provide you a convenient references.

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Your Free Gift

As a way of saying thanks you for your purchase, AI Sciences Publishing Company offering you a free eBook in Machine Learning with Python written by the data scientist Alain Kaufmann.

It is a full book that contains useful machine learning techniques using python. It is 100 pages book with one bonus chapter focusing in Anaconda Setup & Python Crash Course. AI Sciences encourage you to print, save and share. You can download it by going to the link below or by clicking in the book cover above.

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