Machine Learning/Artificial Intelligence/Deep Learning

Purpose

When I started learning Machine Learning, Artificial Intelligence, and Deep Learning, I found myself hard to grasp some ideas related to these fields. Thus, I created this repository as a collection of resources that I used to assist my learning in Machine learning, Artificial Intelligence, and Deep Learning.

AI vs Machine Learning vs Deep Learning

AI is a superset of Machine Learning and Deep Learning. Machine learning is a superset of Deep Learning.

source: edureka!

📖 Books

1. Hands-On Machine Learning with SciKit-Learn & TensorFlow

The book covers a wide range of ML, AI, and DL concepts along with actual codes. It is a great book for beginners who are interested in ML, AI, and DL. However, according to my experience, you should start off by following Coursera Machine Learning Course first. You can just watch the videos in the Week 1 only.

💻 Online Tutorials

1. Coursera Machine Learning Course

This online course provided in Coursera by Standford and DeepLearning.ai is a great place for absolute beginners.

💬 Topics

📊 Convolutional Neural Network

• Simple explanation of Convulutional Neural Network | Deep Learning Tutorial 23 (Tensorflow & Python)

• Best CNN visualization: CNN Explainer

🖼️ Image Embedding

• Image Analytics for Everyone: Image Embeddings with Orange

👀 Discriminative Feature

• What is a discriminative feature?

👥 Siamese Networks

• Siamese Networks section in Contrastive Loss Explained

❗ All Cost Functions

• Understanding Ranking Loss, Contrastive Loss, Margin Loss, Triplet Loss, Hinge Loss and all those confusing names