As things stand, I am nowhere near where I aspire to reach as a Data Scientist. In my journey so far, I have met many helpful people and come across various useful resources.
Whilst I pondered on where I have come from and where I am now, I instantly remembered the 4 books that had been revolutionary for my progress as a Data Scientist – Of which I will be sharing with you today.
Updated 06/10/2020: Hands-On Machine Learning With Scikit-Learn And Tensorflow is copyrighted so I’ve added the link to purchase (sincere apologies to the Author). This means there are only 4 free books as things stand. I’ve been reading to see if there is something that can fill in, if you find something please send your suggestions so I may read through (It must be free please).
Note: There are no affiliate links associated to any of my recommendations and I am in no agreement with any of the authors.
The Hitchhikers Guide to Python
This is an unusual book to start with! Not because it’s controversial or anything, but simply because it is not directly about Data Science.
Python is a popular language among Data Scientist (as well as R), and this book quite literally can take you to expert levels. The book describes the best practices to follow when programming in Python and if you read Data Scientist should know Software Engineering best practices, you’d know this is more important than ever.
More and more Data Science projects are being taken into production which creates a heavy demand on Data Scientist to have more end-to-end skills. This book is a great starter.
You may download this book for free in the link below!
The Hitchhiker’s Guide to Python! – The Hitchhiker’s Guide to Python
Python Data Science Handbook
Jake VanderPlas hit the nail on it’s head with the naming of this book ; It’s one of those "Never throw this book away" books.
From NumPy, to Pandas, to Matplotlib and Machine Learning, Mr. VanderPlas gives a comprehensive overview for how we can face day-to-day challeneges such as manipulating, transforming, and cleaning data; visualizing various kinds of data; and using data to build statistical or machine learning models.
The most Ideal, easy to read reference book!
Hands-On Machine Learning With Scikit-Learn and Tensorflow
Note: It has been brought to my attention that this book is copyrighted, hence technically not making it free – See notes at the top of the page for more details.
The explanations of concepts and coding examples are very intuitive and useful people that want to begin working on personal projects.
In fact, in my opinion, I believe that after reading (or whilst you read) this book it is imperative that you go and build something with your new knowledge.
It is a very practical book and you should most definitely take your time to answer the questions!
To acquire this book please visit Amazon
The Elements of Statistical Learning
Personal Advice? Don’t read this before bed! You want to read it when you have the most energy.
This book is by far the most complex of all the books I’ve suggested and also one that you will be referring back to very often. It dives deep into statistics and is written in quite a complicated manner since it’s heavy on the Math behind many things we will encounter as a Data Scientist.
I’ve put this book here not to show off as if I am smart – I am not, but I can learn anything I want to, just like you! – but to set the standard. If we want to become top Data Scientist, we have to be willing to do things that most people aren’t willing to do such as diving deep into the underpinnings of what holds our field together.
Note: If you aren’t from a Mathematical background, I highly recommend you gain some exposure to Machine Learning algorithms in simpler ways, such as implementing them, before trying to read this one.
Don’t fear the Math, Read The Elements of Statistical Learning.
Machine Learning Yearning
I am quite surprised this book isn’t spoken of as much as some of the other books on this list. Andrew Ng, the Founder of Coursera and the instructor of some of the best courses on Machine Learning and Deep Learning, curated his most valuable lessons from working at companies such as Google and Baidu and put them on paper for us to leech from.
In my personal opinion, after reading a book like ____ which provides us with a practical way of using machine learning, this book is the best book for a super-set. It is about being a great team member which includes being productive, efficient and a great team player (in-case it wasn’t obvious).
Note: To get the free book, you will be asked to fill in some details and it will be emailed to you upon completion.
Bonus Book
As agreed, I’ve given you 4 free books that will take your Data Science skills to the next level. However, as a bonus I will provide __ more books that will take your Data Science skills to the next level – the only difference with th(ese)is book(s) is that they aren’t free. But hey! There is nothing wrong with paying for good quality.
Approaching (Almost) Any Machine Learning Problem
If I had a girlfriend, she’d probably be jealous of my admiration of Abhishek Thakur’s work. One of the most hands on people I have ever come across, it makes sense why he is a Kaggle 4x Grandmaster!
He has released a book that gives us an insight into his world and honestly, it has been one of the best reads – in terms of the amount of practical knowledge I derived from it – this year for me.
Note: The book requires you have good knowledge of Machine Learning so get yourself up to scratch and pick up this bad boy!
Purchase Approaching (Almost) Any Machine Learning Problem on Amazon.
Wrap Up
I’ve summed up books that have taken me to new heights. I have not read all the books surrounding the Data Science field so it’s possible I’ve missed a very important book. If you happen to think this is the case, leave a response with the books title and the free link to the pdf. Many Thanks!
Let’s continue the conversation on LinkedIn…
