ML Fundamentals

Detecting Fast Radio Bursts with Deep Learning

Supervised Machine Learning: Crash Course Statistics #36

Making sense of the confusion matrix

PyTorch Datasets and DataLoaders - Training Set Exploration for Deep Learning and AI

Machine Learning Fundamentals: The Confusion Matrix

ASU Master of Computer Science Live Admissions Q&A

Deep Q-Learning - Combining Neural Networks and Reinforcement Learning

Building AI with TensorFlow: An Overview (TensorFlow @ O’Reilly AI Conference, San Francisco '18)

4. Autoencoders

Natural Language Processing at StockTwits with Garrett Hoffman - TWiML Talk #194

Saving and Loading Models (Coding TensorFlow)

Principal Component Analysis (PCA) - THE MATH YOU SHOULD KNOW!

What is Python? Why Python is So Popular?

Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4

Detecting Faces (Viola Jones Algorithm) - Computerphile

AI Ethics, Strategic Decisioning and Game Theory with Osonde Osoba - TWiML Talk #192

Future Politics | Jamie Susskind | Talks at Google

How convolutional neural networks work, in depth

Support Vector Machines - THE MATH YOU SHOULD KNOW

How optimization for machine learning works, part 4

¿Qué es una Red Neuronal? Parte 3.5 : Las Matemáticas de Backpropagation | DotCSV

Quantum Machine Learning (LIVE)

Quantum Machine Learning (LIVE)

ML Engine - Machine Learning in the Cloud

¿Qué es una Red Neuronal? Parte 3 : Backpropagation | DotCSV

University of Illinois Master of Computer Science: A top-ranked degree that fits your life

These Neural Networks Empower Digital Artists

deeplearning.ai's Heroes of Deep Learning: Dawn Song

Machine Learning Tutorial Part - 1 | Machine Learning Tutorial For Beginners Part - 1 | Simplilearn

CNN Image Preparation Code Project - Learn to Extract, Transform, Load (ETL)

Solve your model’s overfitting and underfitting problems - Pt.2 (Coding TensorFlow)

Dataset for Deep Learning - Fashion MNIST

Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper - TWiML Talk #191

How optimization for machine learning works, part 3

How optimization for machine learning works, part 2

How optimization for machine learning works, part 1

Code for Deep Learning - ArgMax and Reduction Tensor Ops

Solve your model’s overfitting and underfitting problems - Pt.1 (Coding TensorFlow)

Evaluating Model Explainability Methods with Sara Hooker - TWiML Talk #189

TWiML & AI x Fast.ai Deep Learning Study Group - Session 2B - October 6, 2018

TWiML & AI x Fast.ai Deep Learning Study Group - Session 2A - September 29, 2018

Quantum Machine Learning (LIVE)

Graph Analytic Systems with Zachary Hanif - TWiML Talk #188

Tensors for Deep Learning - Broadcasting and Element-wise Operations with PyTorch

The Kernel Trick - THE MATH YOU SHOULD KNOW!

CNN Flatten Operation Visualized - Tensor Batch Processing for Deep Learning

Flatten, Reshape, and Squeeze Explained - Tensors for Deep Learning with PyTorch

Federated ML for Edge Applications with Justin Norman - TWiML Talk #185