My solutions to some of Kaggle Machine Learning competitions. The repository contains 3 sections that divides the problems to 3 difficulties (Easy, Medium, Hard) according to the difficulty i faced during understanding or implementing the problem solution.
Python Packages Used:
Problems Solved:
- [San Francisco Crime Classification] (https://www.kaggle.com/c/sf-crime)
- [Digit Recognizer] (https://www.kaggle.com/c/digit-recognizer)
- [Iris Classification] (https://www.kaggle.com/uciml/iris)
- [Poker Rule Induction] (https://www.kaggle.com/c/poker-rule-induction)
- [What's Cooking] (https://www.kaggle.com/c/whats-cooking)
- [Bike Sharing Demand] (https://www.kaggle.com/c/bike-sharing-demand)
- [Denoising Dirty Documents] (https://www.kaggle.com/c/denoising-dirty-documents/)
- [SMS Spam Collection Dataset] (https://www.kaggle.com/uciml/sms-spam-collection-dataset)