100-Days-of-ML

100 Days of Machine Learning: Documenting My Journey Here 👾

Day 1 -Supervised, Unsupervised, Reinforcement Learning

Type of machine learning: Supervised, Unsupervised, Reinforcement Learning

References:

• https://towardsdatascience.com/reinforcement-learning-101-e24b50e1d292
• https://medium.com/@qjbqvwzmg/understanding-the-three-pillars-of-machine-learning-supervised-unsupervised-and-reinforcement-b3a5317b5612

Day 2 - Real Life Example

Real-life Example

Simple ML coding

Day 3 - Classification VS Regression

Day 4 - Linear Regression

First linear Regression Project here.

Day 5 - Regression Metrics

Day 6 - Multiple Linear Regression

Simple Linear Regression & Multiple Linear Regression here

Day 7 - Logistic Regression

References: https://www.spiceworks.com/tech/artificial-intelligence/articles/what-is-logistic-regression/

Notes Logistic Regression here.

Day 8 - Data Cleaning & Visualization

• Data Cleaning& Visualization code
• Type of plots: https://matplotlib.org/stable/plot_types/index

Day 9 - Build Web App

• UFO's Sightings over the past century
• Tools: Flask, Pickle

Day 10 - Classification

Day 11 - Imbalanced Classification

Day 12- - Confusion Matrix