Summary : This is Machine Learning Piscine(Bootcamp) created by the Paris-based student organization 42AI.
| Module | Title | Description |
|---|---|---|
| 00 | Stepping into Machine Learning | You will start by reviewing some linear algebra and statistics. Then you will implement your first model and learn how to evaluate its performances. |
| 01 | Univariate Linear Regression | Today you will implement a method to improve your model’s performance: gradient descent. Then you will discover the notion of normalization. |
| 02 | Multivariate Linear Regression | Building on what you did on the previous modules you will extend the linear regression to handle more than one features. Then you will see how to build polynomial models and how to detect overfitting. |
| 03 | Logistic Regression | Discover your first classification algorithm: logistic regression. You will learn its loss function, gradient descent and some metrics to evaluate its performance. |
| 04 | Regularization | Today you will fight overfitting! You will discover the concepts of regularization and how to implement it into the algortihms you already saw until now. |