Deep Learning

A collection of learning resources for the AI world

Dataquest - Data Scientist path draft

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

ResNet (Residual Networks) draft

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

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

R-CNN & Fast R-CNN & Faster R-CNN & Mask R-CNN draft

DL by DL.AI — Course 1: NN and DL

DL by DL.AI — Course 4: CNN draft

DL by DL.AI — Course 2: Improving DNN - Tuning, Regularization and Optimization

HOG (Histogram of Oriented Gradients) draft

DL by DL.AI — Course 3: Structuring ML Projects

DL by DL.AI — Course 5: Sequence models draft

Jupyter notebook

Tensorflow

TF by DL.AI — Course 3: NLP in TF

PyTorch draft

TF by DL.AI — Course 2: CNN in TF

TF by DL.AI — Course 4: Sequences, TS, Prediction

TF by DL.AI — Course 1: Intro to TF for AI, ML and DL

Autoencoder draft