If you’re light on a math background, I think reading manga is an entertaining way to fill in your knowledge. Most of the important books that data scientist need to consume require familiarity with the math behind linear regression, arguably the most popular supervised machine learning technique. Chapter 2 covers simple regression (one predictor) and Chapter 2 discusses multiple regression (multiple predictors).

Reading this book might be a nice prelude to diving into a statistical programming environment like R, since topics like ANOVA, confidence intervals, residuals, R-squared, multicollinearity etc. will make a lot more sense. As an added bonus, the book covers binomial logistic regression which is another popular supervised learning method designed to predict probabilities whether or not something will happen.

The book is rather brief with only 216 pages and four chapters:

**Chapter 1:** A Refreshing Glass of Math

**Chapter 2:** Regression Analysis

**Chapter 3:** Multiple Linear Regression Analysis

**Chapter 4:** Logistic Regression Analysis

I already have added a slide to the regular presentation deck I use at conferences for my “Data Science Primer” talk, recommending this book for folks just starting out in the field. I must give kudos to No Starch Press for thinking up this innovative way of teaching a potentially difficult subject. After all, comics have a disarming effect even if the subject is math!

*Contributed by Daniel D. Gutierrez, Managing Editor of insideBIGDATA. In addition to being a big data journalist, Daniel is also a practicing data scientist, educator and sits on a number of advisory boards for various start-up companies.*

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