Frequently Asked Questions
What are the pre-requisites in terms of math and code to make the most of this book?
In terms of math, the book is designed for people without a deep math background. However, you should have some knowledge about basic algebra. For instance, I consider that you understand what equations and mathematical variables are.
In terms of code, the practical aspect of this book leverages the use of code to help you gain insights and mathematical intuition. If you don't have any experience in programming, you'll have trouble to follow along the examples. You could still skip these sections and focus on the plots and text but it is better if you can understand a bit of Python and Numpy.
What will I find in the book that is not on your blog?
I will share around 25% of the book as excerpts on my blog. The goal is to allow readers to check if the book is a fit or not.
I found another book called "Essential Math for Data Science" on Amazon. Is it the same book?
Yes. I started this book with the publisher O'Reilly but our paths diverged and the project aborted. I wanted this book to approach the theoretical concepts needed for data science. The good reviews by readers who got the early release convinced me to publish it by myself.
Due to delays in the update of their references, some book retailers like Amazon (e.g. Amazon France) still propose to pre-order "Essential Math for Data Science" even if it will not be available. I'm very sorry about this confusion.
Can I get help if I have trouble to understand the materials?
Yes, if you buy the "Complete Code" version you get access to the private Github repository and you'll be able to ask any questions as issues. I'll be here and do my best to help you and assist in your learning path.
Will you release a paperback version?
As for now, there is no current plan to do a paperback version of the book. However, tell me (contact@essentialmathfordatascience.com) if this is something you would like to have and I'll reconsider the option if many people are interested.
In what extents the content relates to data science and machine learning?
The math that you need for data science and machine learning have been carefully selected in "Essential Math for Data Science". However, the goal of the book is not to explain the machine learning algorithms themselves but to introduce you to the math you'll need to understand them. These math topics are quite general but the approach is focused on data science: e.g. the hands-on projects at the end of each chapter, the practical examples, the visualizations, etc.
Will I get the next updated versions for free?
Yes. You'll get access to the project anytime (the book that you can download on Gumroad and the notebooks on the private Github repository) and you'll get any future updates.
Is the payment secure?
Yes. I use Gumroad to process the payment and deliver the book and the access to the Github repo (if you buy the Complete Code version).
Do I need to have a Github account to buy the Complete Code version?
Yes. With the Complete Code version, you'll get access to a private Github repository where you'll find the book under the form of Jupyter notebooks. These notebooks (one per chapter) contain the whole code and the whole text of the book. To get the access, you'll need a Github account. Be sure to provide your right Github id (for instance, mine is "hadrienj") in the purchase form (and not the email address). If you don't have a Github account, you can create one easily!
What is Haliotis-Publishing?
I wrote this book as Jupyter Notebooks and found how it is useful to have text and code blocks with outputs like plots. I thus developed a set of tools to convert notebooks into PDF and ebooks and founded Haliotis-Publishing to allow people to write well formated content using notebooks.