This project is a Machine Learning bootcamp created by 42 AI.
As notions seen during this bootcamp can be complex, we very strongly advise students to have previously done the following bootcamp:
42 Artificial Intelligence is a student organization of the Paris campus of the school 42. Our purpose is to foster discussion, learning, and interest in the field of artificial intelligence, by organizing various activities such as lectures and workshops.
Get started with some linear algebra and statistics
Sum, mean, variance, standard deviation, vectors and matrices operations.
Hypothesis, model, regression, cost function.
Implement a method to improve your model's performance: gradient descent, and discover the notion of normalization
Gradient descent, linear regression, normalization.
Extend the linear regression to handle more than one features, build polynomial models and detect overfitting
Multivariate linear hypothesis, multivariate linear gradient descent, polynomial models.
Training and test sets, overfitting.
Discover your first classification algorithm: logistic regression!
Logistic hypothesis, logistic gradient descent, logistic regression, multiclass classification.
Accuracy, precision, recall, F1-score, confusion matrix.
Fight overfitting!
Regularization, overfitting. Regularized cost function, regularized gradient descent.
Regularized linear regression. Regularized logistic regression.
- Amric Trudel ([email protected])
- Maxime Choulika ([email protected])
- Pierre Peigné ([email protected])
- Matthieu David ([email protected])
- Benjamin Carlier ([email protected])
- Pablo Clement ([email protected])
- Richard Blanc ([email protected])
- Solveig Gaydon Ohl ([email protected])
- Quentin Feuillade Montixi ([email protected])
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent