This repository contains some notebooks created using python 3.6 and its main libraries including pandas, numpy and scikit-learn. Most of the notebooks have been done following the online Udemy course 'Python for Data Science and Machine Learning Bootcamp'.
The main topics covered are the following:
- Anomaly Detection
- Linear Regression
- Logistic Regression
- K Nearest Neighbor
- Support Vector Machine
- Decision Tree
- Random Forest
- K Means
- Principal Component Analysis
- Data Visualization
- Recommender System
- Neural Networks
- Natural Language Processing