Free Data Science eBooks - October 2017
The leaves are browning and falling off the trees, the remnants of hurricanes Maria and Lee have just rattled through the UK and there's a chill in the air. Yup, autumn has definitely arrived!
So there's no better time to kick back, get comfy in your favourite armchair with a hot cup of coffee in one hand and some good reading material in the other.
Continuing our Back To School series, here are three free eBooks to help you on your educational journey as the nights get longer, cooler, wetter and windier.
I hope these books prove to be a valuable resource to you and that you will visit regularly (and invite your friends too).
If you haven't subscribed to our newsletter yet, why not subscribe using the form on the right - you'll be the very first to know when new resources are published.
This month, we have Machine Learning, Neural and Statistical Classification, Report writing for Data Science in R and An Introduction to Statistical Learning with Applications in R. They're all FREE, so help yourselves.
by D. Michie, D.J. Spiegelhalter, C.C. Taylor (eds)
The aim of this book is to provide an up-to-date review of different approaches to classification, compare their performance on a wide range of challenging data-sets, and draw conclusions on their applicability to realistic industrial problems.
As the book's title suggests, a wide variety of approaches has been taken towards this task. Three main historical strands of research can be identified: statistical, machine learning and neural network.
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by Roger D. Peng
This book teaches the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducibility is the idea that data analyses should be published or made available with their data and software code so that others may verify the findings and build upon them. The need for reproducible report writing is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.
Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available.
This book will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.
by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
This book provides an introduction to statistical learning methods.
It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.
The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist.
If you're interested in learning more about the content in this blog post we've sought out the best blogs, books, video courses and other stuff from around the internet for you. Some may be free while others may not, and to help you decide we use the following ratings:
- FREE content
- costs less than 10 £/$/Euro
- costs less than 50 £/$/Euro
- costs less than 100 £/$/Euro
- costs more than 100 £/$/Euro
Disclosure: some of these resources may be affiliate links, and we may earn an affiliate commission for purchases you make when using these links
You can find further details in our TCs
Practical Data Cleaning - 19 Essential Tips to Scrub Your Dirty Data
It's always difficult knowing where to start, but especially so when it comes to Data Science. No need to fret, though - we've selected our top 21 books that all aspiring data scientists should read.
These will get you going in no time...
Correlation and Causation - The Trouble With Story Telling
How many times have you heard that ‘correlation does not imply causation’? Lots, but I bet you didn't know that there are five reasons why you should not trust your intuition. This book gives you the tools to discover the five traps that even experienced investigators fall into.
Videos & Video Courses
4 hour Udemy Video Course delivered with animated videos. Perfect for beginners and will help get you started with basic statistical concepts
7 hour Udemy Video Course. Great for those needing a more business-oriented introduction to stats. Better still, the course even comes with homework. Yay!
9 hour Udemy Video Course. This is one of the top stats courses at Udemy and is a must-see for those that need to learn stats in R
CorrelViz - visualise all the correlations in your data in minutes
CorrelViz is completely automated and gives you the Story of Your Data in minutes, with one click - saving you months of manual analysis and shed-loads of cash!
Analyse all your data, discover all the correlations you seek - and some you never even dreamed of...
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