Machine Learning

Jupyter notebook

DS & ML with Mac M-chip

A workflow for creating a Docker image with support for TensorFlow, PyTorch, and GPU

Reading: Hands-On ML - Chap 1: The ML Landscape

Reading: Hands-On ML - Quick notes (Chapter 14 & 15)

[archived] Resources for DS & ML & DL

Reading: Hands-On ML - Chap 2: End-to-End ML Project

Reading: Hands-On ML - Chap 3: Classification

Reading: Hands-On ML - Quick notes (Chapter 10 — 13)

Reading: Hands-On ML - Quick notes (Chapter 4 — 9)

HOG (Histogram of Oriented Gradients)draft

Metrics for clustering

Principal Component Analysis (PCA)

Decision Tree Classifier

Support Vector Machine (SVM)

Confusion matrix & f1-score

Tensorflow

Undefitting & Overfittingdraft

Dynamic Time Warping (DTW)

Mean Shift clustering

DBSCAN / HDBSCAN Clustering

Pipeline & GridSearchdraft

Random Forest

Decision Tree Regression

K-Means & K-Medoids Clustering