Feature Engineering for Machine Learning
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists Feature Engineering for Machine Learning: The following is a review of t...
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists Feature Engineering for Machine Learning: The following is a review of t...
Bayes Theorem Explained: A simple introduction to one of the most important concepts of probability theory. Check it out!
Looking for a tidy but accesible list of the main Machine Learning algorithms and models? Then read on!
What is Transfer Learning? Where can I use it? Why should I use it? What are some examples? Read On to find out!
Learn why Feature Scaling is a fundamental part of building an unsupervised learning model with a clear example!
Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD The following is a review of the great fastai python book by Jeremy Howard &...
Practical Natural Language Processing Book: The Natural Language Processing book for everybody. Read our review and find out why!
What is Pattern Recognition? How is it related to Machine Learning? Answer these questions and a lot more with the famous book Pattern Recognition and Machine L...
An amazing introduction to how Deep Learning works under the hood, a small glance of what is inside the black box of Artificial Neural Networks: Grokking Deep L...
Learn what feature selection is, why it is important, and how you can use it.