📌 Brief introduction to the curriculum
0. What is Machine Learning (ML)?
- Let's get a firm grasp of the concepts of machine learning.
1. A simple practice environment that does not require complex installation.
2. Introduction to scikit-learn & My First Machine Learning Model
- Let's predict weight based on height.
3. Introduction to Kaggle and Kaggle Competition
4. Linear Regression Algorithm (Ridge, Lasso, ElasticNet) & How Much is My House Worth?
- Let's predict Boston real estate prices.
5. Random Forest, a popular and powerful predictor
- Let's predict whether it will rain tomorrow using a machine learning model.
6. XGBoost, the algorithm favored by Kaggle winners
- Let's predict the occurrence of a stroke using XGBoost.
7. Practical Stories from a Machine Learning Engineer
- Experience the daily life of a machine learning engineer.
8. Practical DS/ML Tips from Professionals