ML Fundamentals

L13.6 CNNs & Backpropagation

Lux - Python Library for Intelligent Visual Discovery

Project InnerEye: Augmenting cancer radiotherapy workflows with deep learning and open source

ProGAN implementation from scratch

Build by Small Pieces // Igor Lushchyk // MLOps Meetup #55 short clip

Autoencoder In PyTorch - Theory & Implementation

Devops Vs MLOPS- Understand The Differences And Why IT is Important

Operationalizing Machine Learning at a Large Financial Institution // Daniel Stahl //MLOps Meetup#56

MARCH MADNESS - Will My Machine Learning Model Beat Your Bracket?

L13.4 Convolutional Filters and Weight-Sharing

ProGAN Paper Walkthrough

Should You Scale Your Data ??? : Data Science Concepts

The Discovery That Transformed Pi

Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 1/2

How Shazam Works (Probably!) - Computerphile

Me he CAPTURADO en 3D... ¡DENTRO de una Red Neuronal! (y tú también puedes 👀)

Oxford Africa Business Alliance Student Webinar: Oxford MBA

Coding SVM Kernels : Data Science Code

How you SHOULD code Machine Learning

Artificial intelligence Or Machine Learning #Shorts

Will AI replace network engineers?

Convolutional Autoencoder for Image Denoising - Keras Code Examples

Converting words to numbers, Word Embeddings | Deep Learning Tutorial 39 (Tensorflow & Python)

Day 4- MLOPS Continuous Integration And Model Tracking Using MLFlow- Machine Learning

L13.3 Convolutional Neural Network Basics

L13.0 Introduction to Convolutional Networks -- Lecture Overview

Day 3- MLOPS End To End Implementation With Deployment- Machine Learning

Day 2- MLOPS End To End Implementation From Basics- Machine Learning

L12.6 Additional Topics and Research on Optimization Algorithms

L12.5 Choosing Different Optimizers in PyTorch

L12.4 Adam: Combining Adaptive Learning Rates and Momentum

L12.3 SGD with Momentum

L12.2 Learning Rate Schedulers in PyTorch

L12.1 Learning Rate Decay

L12.0: Improving Gradient Descent-based Optimization -- Lecture Overview

Day 1- MLOPS End To End Implementation- Machine Learning

CycleGAN implementation from scratch

TensorFlow DCGAN Tutorial

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

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