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.
Understand useful mathematical functions and formulas
Sum, mean, variance, standard deviation, vectors and matrices operations.
Get started with the first concepts constituting the field of Machine Learning
Matrix operations, gradient descent, cost function, normal equation, MSE, RMSE R-score and learning rate.
Implement a Logistic Regression class using a Gradient Descent algorithm
Sigmoid, log loss, gradient descent, logistic regression, model evaluation, confusion matrix.
See the L2 regularization and a few ways to process your data in order to improve significantly the performance of your models!
Regularization, regularized linear regression, regularized logistic regression, Z-score standardization, min-max standardization, polynomial features, interaction terms.
Be able to use Decision Trees algorithms wisely in the future
Gini impurity, entropy, information gain and decision trees.
- 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