The book every data scientist needs on their desk.

Machine/Deep Learning metrics implementation in python

You can find here the implementation of my knowledge of basic machine learning algorithms and metrics, data analysis, and applying hyperparametric optimization techniques to improve model performance.

Backtesting trading strategy performances between actual market returns, a dual moving average crossover strategy and support vector machines

The current repository contains ml works that were completed on the course and independently. These include the use of the most popular methods for solving forecasting problems (linear regression, polynomial regression, regression with L1 and L2 regularization), classification (k-nearest neighbor method, decision trees, naive Bayesian classifier…