For the third meetup on 6th May
- We will practice what we already discussed including
- Different data preprocessing techniques
- Feature Selection approaches
- Improve our linear regression model (parameter tuning)
- Feature transformation and feature engineering
- Revision on Feature Selection approaches, Parameter tuning (available as kernel series for prepractice)
- Unsuppervised methods
- Hands-on - A kaggle kernel series
- Link Back to Main Page
- Link For Reporting Issues or Initiate Discussion
- Link Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow by Sebastian Raschka (highly recommended book)
- Link An Introduction to Statistical Learning with Applications in R (recommended book)
- List of Free Data Science Books
