ML Fundamentals

Look Mom, No Indices! Vector Calculus with the Fréchet Derivative by Charles Frye

Sequence Models with Pujaa Rajan

How to Transition into Data Science: from Computer Science to Data Science

MLOps Meetup #6: Mid-Scale Production Feature Engineering with Dr. Venkata Pingali

Intro to Deep Learning -- L15 Autoencoders [Stat453, SS20]

Decoding Logistic Regression - A Simple and Comprehensive Explanation

How deep learning can detect cancerous tissue (AI For Medicine)

Automate LifeCycle Of Data Science Projects By Using This Open Source Library

Intro to Deep Learning -- L14 Intro to Recurrent Neural Networks [Stat453, SS20]

R Tutorial: Nonlinear Modeling in R with GAMs | Intro

Pytorch ResNet implementation from Scratch

PyTorch Tutorial 17 - Saving and Loading Models

Teachable Machine By Google- Train Your Model With Ease

Python Tutorial: Introducing convolutional neural networks

Demystifying Data Mining - A Clear and Concise Explanation

This Neural Network Learned To Look Around In Real Scenes! (NERF)

Neural Networks from Scratch - P.1 Intro and Neuron Code

Pytorch Quick Tip: Using a Learning Rate Scheduler

Optimization - Lecture 3 - CS50's Introduction to Artificial Intelligence with Python 2020

Uncertainty - Lecture 2 - CS50's Introduction to Artificial Intelligence with Python 2020

How to Transition Into Data Science: From Economics to Data Science

Why use GPU with Neural Networks?

Ask a Machine Learning Engineer Anything (live) | April 2020

Python Tutorial: Image classification with Keras

Python Tutorial: Classifying images

Python Tutorial : Data transforms, features, and targets

Python Tutorial : Linear modeling with financial data

Python Tutorial : Machine Learning for Finance in Python

R Tutorial : Network analysis in R: A tidy approach

PyTorch Tutorial : Backpropagation by auto-differentiation

PyTorch Tutorial : Introduction to PyTorch

PyTorch Tutorial : Introduction to Neural Networks

PyTorch Tutorial : Forward propagation

Python Tutorial : Writing Efficient Python Code

Python Tutorial : Introducing XGBoost

Python Tutorial: Class distribution

Knowledge - Lecture 1 - CS50's Introduction to Artificial Intelligence with Python 2020

Learning - Lecture 4 - CS50's Introduction to Artificial Intelligence with Python 2020

Neural Networks - Lecture 5 - CS50's Introduction to Artificial Intelligence with Python 2020

Pytorch Quick Tip: Weight Initialization

Pytorch Data Augmentation using Torchvision

Feature Engineering-How to Transform Data to Better Fit The Gaussian Distribution-Data Science

Data Science Demystified - An Essential Introduction

Intro to Deep Learning -- L13 Intro to Convolutional Neural Networks (Part 2) 2/2 [Stat453, SS20]

Python Tutorial : When should I use XGBoost?

Pytorch Transfer Learning and Fine Tuning Tutorial

Intro to Deep Learning -- L13 Intro to Convolutional Neural Networks (Part 2) 1/2 [Stat453, SS20]

Rachael Tatman — Conversational AI and Linguistics