I received an e-mail from Kaggle asking me to participate in '30 Days of ML'. I participated in the course to review and organize the machine learning skills and Python grammar that I have learned so far.
In the first 2 weeks, I received hands-on assignments delivered to my inbox. The goal of these assignments is to rapidly cover the most essential skills needed to get your hands dirty with data. I started by learning how to code in Python and quickly learn how to build my first machine learning model. And then, I participated in the 30 Days of ML competition.
Here in this repository, you can see the notebooks that I have written and type up for 30 days of assignments and competitions from Kaggle.
The dataset is used for this competition is synthetic (and generated using a CTGAN), but based on a real dataset. The original dataset deals with predicting the amount of an insurance claim. Although the features are anonymized, they have properties relating to real-world features.
📚 2 weeks of daily, hands-on assignments (with emails to keep you on track) 📃 Course completion certificates 💬 Learning community chat room access 🎥 Elective workshops by Google's Developer Expert Data Science Program ⛰️ Invitation to a beginner-friendly, invite-only Kaggle competition 🏆 Competition prizes (Kaggle Swag for top 10 teams on leaderboard)
- Hands-on assignments : Python, Intro to Machine Learning, Intermediate Machine Learning (kaggle courses)
- 30 Days of ML : https://www.kaggle.com/thirty-days-of-ml
- 30 Days of ML Competition : https://www.kaggle.com/c/30-days-of-ml