ML Fundamentals

How to Avoid Suffering in MLOps/Data Engineering Role // Igor Lushchyk // MLOps Meetup #55

MLOps Live Community Session Announcement

L11.7 Weight Initialization in PyTorch -- Code Example

L11.6 Xavier Glorot and Kaiming He Initialization

Dave Selinger — AI and the Next Generation of Security Systems

Waste Classification Machine Learning Classification Project-Waste Recycling

CycleGAN Paper Walkthrough

Pix2Pix implementation from scratch

AI and Gaming Research Summit 2021 - Understanding Players (Day 2 Track 1.2)

Expectations with Machine Learning

PyTorch Time Sequence Prediction With LSTM - Forecasting Tutorial

Level up your software engineering skills as a data scientist | ML Monthly February 2021

Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs)

Machine Learning Frameworks - The Landscape

How to Learn DATA SCIENCE Ridiculously FAST

Python Tutorial for Beginners - Learn Python in 5 Hours [FULL COURSE]

PIE & AI Kigali – Building a Career in Data Science: From Learning to Landing a Job

Cal Newport: Deep Work, Focus, Productivity, Email, and Social Media | Lex Fridman Podcast #166

Intro to Deep Learning (ML Tech Talks)

Does anyone know of a good way to manage dependencies? // MLOps Coffee Sessions #31 Part 2 Clip

Petroleum Engineer To Data Scientist

Outliers : Data Science Basics

Autoencoders in Python with Tensorflow/Keras

Neural Networks Part 7: Cross Entropy Derivatives and Backpropagation

AutoNLP Preview: Auto model-selection, fine-tuning and deployment of state-of-the-art NLP models

L11.5 Weight Initialization -- Why Do We Care?

L11.4 Why BatchNorm Works

L11.3 BatchNorm in PyTorch -- Code Example

L11.2 How BatchNorm Works

L11.1 Input Normalization

L11.0 Input Normalization and Weight Initialization -- Lecture Overview

L10.5.4 Dropout in PyTorch

L10.4 L2 Regularization for Neural Nets

L10.2 Data Augmentation in PyTorch

L10.0 Regularization Methods for Neural Networks -- Lecture Overview

How (and why) you should undervolt your GPU - A step by step guide (Deep Learning/Gaming/Mining)

L9.5.2 Custom DataLoaders in PyTorch --Code Example

L9.5.1 Cats & Dogs and Custom Data Loaders

L9.4 Overfitting and Underfitting

Pix2Pix Paper Walkthrough

Amazing Data Science End To End Project From Starters In ML and Deep Learning- Agriculture Domain

L9.3.3 Multilayer Perceptron in PyTorch -- Code Example Part 3/3 (Script Setup)

L9.3.2 Multilayer Perceptron in PyTorch -- Code Example Part 2/3 (Jupyter Notebook)

L9.3.1 Multilayer Perceptron -- Code Example Part 1/3 (Slide Overview)

L9.2 Nonlinear Activation Functions

L9.1 Multilayer Perceptron Architecture

L9.0 Multilayer Perceptrons -- Lecture Overview

Neural Networks Part 6: Cross Entropy