Approaching (Almost) Any Machine Learning Problem 2020

The book is for you if you are looking for guidance on approaching machine learning problems. The book is best enjoyed with a cup of coffee and a laptop/workstation where you can code along.

Table of contents:

– Setting up your working environment
– Supervised vs unsupervised learning
– Cross-validation
– Evaluation metrics
– Arranging machine learning projects
– Approaching categorical variables
– Feature engineering
– Feature selection
– Hyperparameter optimization
– Approaching image classification & segmentation
– Approaching text classification/regression
– Approaching ensembling and stacking
– Approaching reproducible code & model serving

There are no sub-headings. Important terms are written in bold.
I will be answering all your queries related to the book and will be making YouTube tutorials to cover what has not been discussed in the book. To ask questions/doubts, please create an issue on github repo: https://github.com/abhishekkrthakur/approachingalmost