Summary: Recurrent Neural Nets (RNNs) are at the core of the most common AI applications in use today but we are rapidly recognizing broad time series problem types where...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
The key to perform any text mining operation, such as topic detection or sentiment analysis, is to transform words into numbers, sequences of words into sequences of numb...
For one- or two-semester business statistics courses. Not a new book, but a popular one (8th edition.) This text is the gold standard for learning how to use Excel in b...
Introduction Are you looking to learn python for data science but have a time crunch? Are you making your career shift into data science and want to learn python? In this...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Why is data so important? Despite being about as prevalent as electricity, it can be difficult to adequately explain how critical data is to the modern world. From busine...
Summary: Contextually intelligent, NLP-based interactive assistants are one of the next big things for AI/ML. The tech is already here from recommendation engines. ...
This post is part of my forthcoming book The Mathematical Foundations of Data Science. Probability is one of the foundations of machine learning (along with linear algebr...
You have probably heard about the concept of massive open online courses (MOOC’s) in the last few years. It is an alternative to formal education and is seen by som...