As a senior datascience professional and analytics manager, I get countless requests for job search advice, resume feedback and heart-breaking stories from brilliant stud...
Cross Validation explained in one simple picture. The method shown here is k-fold cross validation, where data is split into k folds (in this example, 5 folds). Blue ball...
Digital capabilities leverage customer, product and operational insights to digitally transform business models. And nowhere is this more evident than the rush by indus...
Our Telecom Client was developing a Big Data Product that will profile demography (Age, Gender, Income, Ethnicity, Marital Status) of the visitors of the stores receiving...
I stumbled upon this book by chance, when searching for material about time series (probably the most interesting chapter in this collection.) The various chapters are ac...
The following notes represent a complete, stand alone interpretation of Stanford’s machine learning course presented by Professor Andrew Ng and originally posted ...
By Avrim Blum, John Hopcroft, and Ravindran Kannan (2018). Computer science as an academic discipline began in the 1960s. Emphasis was on programming languages, compile...
Not to be confused with this free Microsoft book with same title. Data science underlies Amazon’s product recommender, LinkedIn’s People You Know feature, Pa...
There are plenty of resources on the Internet to learn linear algebra or to get a refresher, including our own tutorial (here). Below are three interesting books found on...
This glossary defines general machine learning terms as well as terms specific to TensorFlow. Below is a small selection of the most popular entries. You can access this ...