v0.21

Expanded outlook on machine learning

• restructured outlook on machine learning (+ refs)
• minor textual changes

v0.20

Add principle limitations of dimensionality reduction

• added example of 3D --> 2D loss of information

v0.19

Add community detection

• Edits to the network analysis/graph sections
• Addition of sections on community detection with Python plots and two example algorithms (Girvan-Newman and Louvain) together with the concept of modularity.

v0.18

Update of NLP chapters

• expansions and improvements of NLP chapter on work vectors and n-grams.
• additional references
• edits to intro
• renaming of all book and notebook files

v0.17

NLP related updates

• added logistic regression to linear models chapter
• cleaned and edited text in NLP chapters
• edited figures in NLP chapters
• add Spacy pattern search example

v0.16

General updates, more ML and NLP

• multiple references added
• larger text edits in many chapters
• larger code additions to illustrate bagging and boosting
• cleaning and fixes of first NLP chapters

v0.15.1

Add ensemble models and edits

• Add wrap up chapter including ensemble models (bagging & boosting)
• Add references
• Minor to moderate edits

v0.15

Addition of missing machine learning key techniques

• added more on evaluation metrics
• added cross-validation
• added grid search
• added obesity data and hands-on example
• added binder and google colab buttons

v0.14

Addition of missing machine learning parts (mostly)

• Added chapter on decision trees
• edits on other machine learning chapters
• still missing: random forest, more model evaluation, scikit-learn pipeline

v0.13

Larger edits on dimensionality reduction

• added illustrative figures
• expand text and documentation
• include umap example
• general editing and cleaning