Machine Learning Tucson, Az (work in progress)

Official Syllabus for Machine Learning - Saturdays.ai

To work with this notebooks you can:

1. clone the repo to your computer git clone https://github.com/SaturdaysAI-Tucson/Machine-Learning
2. Execute it online on Google Colab.
3. Execute it online with Jupyter and mybinder.

To get the certificate of completion with the mention "Machine Learning", you need to finish the entire sillabus.

Stage 1: Code to learn

#1 - Cleaning & Exploratory Data Pandas:
Objetive: Get familiarized with Pandas, how to clean and explore data. Data structure with python.

Session 1. Python Crash Course.

• Notebook

Session 2. Pandas and Numpy

Session 3. Data Visualization

Session 4. Linear Regressions

Session 5. Logistic Regressions

Session 6. CHALLENGE / Guest Speaker

Session 7. Desicion Trees and Random Forest

Session 8. In-depth Random Forest

Session 9 . KNN and KMeans

Stage 2: Build to learn

Session 10 . Build to Learn - Work on your project.

Session 11 . Build to Learn - Work on your project.

Session 12 . Build to Learn - Work on your project.

Session 13 . Build to Learn - Work on your project.

Session 14 . Build to Learn - Work on your project.

DEMO DAY