Deep Learning

Blog posts

A collection of learning resources for the AI world
A workflow for creating a Docker image with support for TensorFlow, PyTorch, and GPU

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

Dataquest - Data Scientist path draft

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

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

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

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

Reading: Hands-On ML - Chap 3: Classification

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

Note for couse DL 4: CNN draft

ResNet (Residual Networks) draft

HOG (Histogram of Oriented Gradients) draft

Note for couse DL 1: NN and DL

DS & ML with Mac M1

Note for couse DL 2: Improving DNN: Tuning, Regularization and Optimization

Jupyter notebook

Tensorflow

Resources for DS & ML & DL

Note for couse DL 5: Sequence models draft

Note for course TF 3: NLP in TF

PyTorch draft

Note for course TF 2: CNN in TF

Note for course TF 4: Sequences, TS, Prediction

Note for course TF 1: Intro to TF for AI, ML and DL

Note for couse DL 3: Structuring ML Projects

Autoencoder draft