This course provides a conceptual framework and practical insights to work in the Machine Learning field using python programming language. The content of the tutorial combines theoretical concepts with programming examples about how to use these algorithms through the Scikit learn library from Python. All the examples are related to the application of machine learning in the finance domain.

Machine Learning in Finance Using Python

Lessons

Machine Learning with Python

What is Machine Learning?

Data Preprocessing in Data Science and Machine Learning

Feature Selection in Machine Learning

Train-Test Datasets in Machine Learning

Evaluate Model Performance - Loss Function

Model Selection in Machine Learning

Bias Variance Trade Off

Supervised Learning Models

Multiple Linear Regression

Logistic Regression

Logistic Regression in Python using scikit-learn Package

Decision Trees in Machine Learning

Random Forest Algorithm in Python

Support Vector Machine Algorithm Explained

Multivariate Linear Regression in Python with scikit-learn Library

Classifier Model in Machine Learning Using Python

Cross Validation to Avoid Overfitting in Machine Learning

K-Fold Cross Validation Example Using Python scikit-learn

Unsupervised Learning Models

K-Means Algorithm Python Example

Neural Networks Overview

Master Data & AI for Finance