Bootcamp proposed by 42AI association, now available as a after common-core project at Paris 42 school.
Please, find more informations and credits at 42AI corresponding page
A one week bootcamp to learn machine learning using Stanford massive open online course (MOOC) on Machine Learning as main resource.
Get started with some linear algebra and statistics
Sum, mean, variance, standard deviation, vectors and matrices operations.
Hypothesis, model, regression, loss 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 loss function, regularized gradient descent.
Regularized linear regression. Regularized logistic regression.
- Numpy
- matplotlib
- pandas
- sklearn
