Data Science Reading List

Data Science, Business Intelligence, Predictive Analytics, or whatever you call it.  There is a wealth of knowledge out there, much of it written decades before “Data Science” became a term!  This list is far from comprehensive and will undergo changes as I find more books.

Enjoy your journey toward data mining mastery!

The Short List:

If you have the urge to binge on a small amount of books, here are my top of the top picks.  Reading these few books will take you from beginner to pro in no time.

Using Statistical Software

Core books to learn the software used in data manipulation and statistical analysis

Business Concepts and Data

Sometimes you don’t need all of the details on implementation or using a particular tool.

Reporting and Visualization

The softer side of data mining but definitely more important than finding the “perfect” algorithm for your application.  Writing well and presenting your results are more than half the battle in analysis.

Detailed Data Mining References

If you want to know what each algorithm is really doing and how to get the most out of your model development, you’ll need a solid academic reference book.

Implementing Algorithms

Getting your hands dirty with algorithms is a great way to learn the inner workings of machine learning models and can be a great experience.

Big Data, Distributed Databases

The wave of the future is analyzing huge datasets.  Spark and (to some extent) Hadoop are important tools to understand well.

Testing and Web Analytics

Having the best machine learning algorithms in the palm of your hand won’t do you any good if you’re not sure how to successfully test their performance.  Web analytics become an important point as they will be a great source of data for your models.

Stories About Statistics

If you’re like me, it’s fun to read about analytics and problem solving with numbers.  Take a break from learning your next language or algorithm and read something easy and fun!