📐 ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

ML Fundamentals

Leadership in Extraordinary Times S3E5: The Great Decoupling

Saïd Business School, University of Oxford Intermediate 5y ago

ML Fundamentals

Leadership in Extraordinary Times S3E6: Saints or Sinners?

Saïd Business School, University of Oxford Intermediate 5y ago

ML Fundamentals

Texthero-Text Preprocessing, Representation And Visualization From Zero to Hero.

Krish Naik Beginner 5y ago

ML Fundamentals

A Chat with Andrew on MLOps: From Model-centric to Data-centric AI

DeepLearningAI Beginner 5y ago

ML Fundamentals

Word embedding using keras embedding layer | Deep Learning Tutorial 40 (Tensorflow, Keras & Python)

codebasics Beginner 5y ago

ML Fundamentals

L13.9.3 AlexNet in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.9.2 Saving and Loading Models in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

DeepLearningAI Live Stream

DeepLearningAI Beginner 5y ago

ML Fundamentals

Lux - Python Library for Intelligent Visual Discovery

Krish Naik Beginner 5y ago

ML Fundamentals

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

Microsoft Research Advanced 5y ago

ML Fundamentals

ProGAN implementation from scratch

Aladdin Persson Beginner 5y ago

ML Fundamentals

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

MLOps.community Beginner 5y ago

ML Fundamentals

Autoencoder In PyTorch - Theory & Implementation

Patrick Loeber Beginner 5y ago

ML Fundamentals

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

MLOps.community Beginner 5y ago

ML Fundamentals

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

Ken Jee Beginner 5y ago

ML Fundamentals

ProGAN Paper Walkthrough

Aladdin Persson Beginner 5y ago

ML Fundamentals

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

ritvikmath Intermediate 5y ago

ML Fundamentals

The Discovery That Transformed Pi

Veritasium Advanced 5y ago

ML Fundamentals

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

Daniel Bourke Beginner 5y ago

ML Fundamentals

How Shazam Works (Probably!) - Computerphile

Computerphile Intermediate 5y ago

ML Fundamentals

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

Dot CSV Beginner 5y ago

ML Fundamentals

Coding SVM Kernels : Data Science Code

ritvikmath Intermediate 5y ago

ML Fundamentals

How you SHOULD code Machine Learning

CodeEmporium Beginner 5y ago

ML Fundamentals

Artificial intelligence Or Machine Learning #Shorts

Manish Sharma Beginner 5y ago

ML Fundamentals

Oxford High Performance Leadership Programme | Ethos and Virtual Design

Saïd Business School, University of Oxford Advanced 5y ago

ML Fundamentals

L13.9.1 LeNet-5 in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.8 What a CNN Can See

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.7 CNN Architectures & AlexNet

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.6 CNNs & Backpropagation

Sebastian Raschka Beginner 5y ago

ML Fundamentals

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

Krish Naik Beginner 5y ago

ML Fundamentals

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

Krish Naik Beginner 5y ago

ML Fundamentals

L13.4 Convolutional Filters and Weight-Sharing

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.3 Convolutional Neural Network Basics

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.1 Common Applications of CNNs

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.0 Introduction to Convolutional Networks -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals

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

Krish Naik Beginner 5y ago

ML Fundamentals

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

Krish Naik Beginner 5y ago

ML Fundamentals

L12.6 Additional Topics and Research on Optimization Algorithms

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.5 Choosing Different Optimizers in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.4 Adam: Combining Adaptive Learning Rates and Momentum

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.3 SGD with Momentum

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.2 Learning Rate Schedulers in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.1 Learning Rate Decay

Sebastian Raschka Beginner 5y ago

ML Fundamentals

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

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Day 1- MLOPS End To End Implementation- Machine Learning

Krish Naik Beginner 5y ago

ML Fundamentals

Digital Platforms: Saints or Sinners?

Saïd Business School, University of Oxford Advanced 5y ago

ML Fundamentals

CycleGAN implementation from scratch

Aladdin Persson Beginner 5y ago

ML Fundamentals

Oxford Africa Business Alliance Student Webinar: Oxford MBA

Saïd Business School, University of Oxford Intermediate 5y ago