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Data Science From Scratch With Python: Step-by-Step Guide
If you are looking for a complete step-by-step guide to data science using Python from scratch, this book is for you.
After his great success with his first book “Data Analysis from Scratch with Python”, Peter Morgan publishes his second book focusing now in data science and machine learning. It is considered by practitioners as the easiest guide ever written in this domain.
Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch.
To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach, which would lead to better mental representations.
The Book give complete instructions for manipulating, processing, cleaning, modeling and crunching datasets in Python. This is a hands-on guide with practical case studies of data analysis problems effectively. You will learn, pandas, NumPy, IPython, and Jupiter in the Process.
Target Users
The book is designed for a variety of target audiences. The most suitable users would
Part 1: Data Science Fundamentals, Concepts and Algorithms
Part 2: Data Science in Practice
Does this book include everything I need to become a data science expert?
Unfortunately, no. This book is designed for readers taking their first steps in data science and machine learning using Python and further learning will be required beyond this book to master all aspects.
Can I have a refund if this book doesn’t fit for me?
Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email.
After his great success with his first book “Data Analysis from Scratch with Python”, Peter Morgan publishes his second book focusing now in data science and machine learning. It is considered by practitioners as the easiest guide ever written in this domain.
Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch.
To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach, which would lead to better mental representations.
The Book give complete instructions for manipulating, processing, cleaning, modeling and crunching datasets in Python. This is a hands-on guide with practical case studies of data analysis problems effectively. You will learn, pandas, NumPy, IPython, and Jupiter in the Process.
Target Users
The book is designed for a variety of target audiences. The most suitable users would
Part 1: Data Science Fundamentals, Concepts and Algorithms
Part 2: Data Science in Practice
Does this book include everything I need to become a data science expert?
Unfortunately, no. This book is designed for readers taking their first steps in data science and machine learning using Python and further learning will be required beyond this book to master all aspects.
Can I have a refund if this book doesn’t fit for me?
Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email.
139 pages, Kindle Edition
Published July 2, 2018
23 people are currently reading
44 people want to read
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Displaying 1 - 3 of 3 reviews
November 20, 2018
Great Data science book for starters
I recommend this book for people who wants to have a general knowledge for data science. The author uses simple English language to make it easier to understand. Also uses very good simple example of python codes.
I would love to have more practical example to get more hands on experience.
I recommend this book for people who wants to have a general knowledge for data science. The author uses simple English language to make it easier to understand. Also uses very good simple example of python codes.
I would love to have more practical example to get more hands on experience.
December 22, 2018
Gentle introductory text. A few typos, but overall well structured.
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May 16, 201951
Displaying 1 - 3 of 3 reviews