This repository is used to store my progress in Jose Portilla's Udemy course on Python applied to Data Science and Machine Learning. Each folder contains not only the lectures, but also my own notes and experiments with the given datasets.
Topics covered in the course are:
- Python pratice (NumPY, Pandas)
- Visualization libraries (Matplotlib, Seaborn, Plotly, Cufflinks)
- Exploratory analysis
- Machine Learning Algorithms (SciKit Learn)
- Linear Regression
- Logistic Regression
- KNN
- Decision Tress and Random Forests
- SVM
- K-Means Clustering
- PCA
- Recommender Systems
- NLP -Neural Nets/Deep Learning
- Big Data and Spark (PySpark)