ML Fundamentals

Discrete & Continuous random variables

NVIDIA GET3D: AI Model to Populate Virtual Worlds with 3D Objects and Characters

Creating Stable Diffusion Interpolation Videos

Variational Autoencoder from scratch in PyTorch

The Road Ahead: Google's Comprehensive Platform for Open Source Machine Learning

Productionizing Machine Learning Models at Scale with Kubernetes

NVIDIA RecSys Summit 2022 - China Day

Model Quantization for Edge Devices with AIMET

Active Learning. The Secret of Training Models Without Labels.

At the Frontiers of Science: Exciting Advances in Protein Design

Day 3 Panel “Trends and the Technological Cutting Edge" - Summary

Designing Machine Learning Systems | book summary | Read a book with me

Deploy a custom Machine Learning model to mobile

Why leaders come on the Oxford High Performance Leadership Programme

Python Plays GTA V: Reboot - Announcement

Andrew Brock on Generative Models and His Journey to AI Research

Machine Learning bias example

Coding PCA from Scratch : Data Science Code

Research talk: Maia Chess: A human-like neural network chess engine

JAX MD: A Framework for Differentiable Atomistic Physics

Does Model Performance Even Matter?

Bike Share Demand Forecasting

The Not So Talked About Reasons Model Monitoring Fails // Oren Razon // MLOps Meetup #88

Equivariant Priors for Compressed Sensing with Arash Behboodi - #584

The Rise of DeBERTa for NLP Downstream Tasks | Grandmaster Series E7

An introduction to MLOps with TensorFlow Extended (TFX)

Oxford High Performance Leadership Programme - Karen Chan

Oxford High Performance Leadership - Susanna Pertl

Oxford High Performance Leadership - Chris Hill

Modern Medical Image Segmentation, AutoML, and Beyond

Meg's realization of the importance of Ethical AI

Advice for Women in AI/Machine Learning

Hello Sionna! A Demo of The First Open Source Library for Physical Layer Research

Full-Stack AI Systems Development with Murali Akula - #563

The path to net zero: Why and how for business and financial markets

Research talk: Torchy: A tracing JIT compiler for PyTorch

Research talk: Causal learning: Discovering causal relations for out-of-distribution generalization

Keynote: Unlocking exabytes of training data through privacy preserving machine learning

Opening remarks: Cloud Intelligence/AIOps

Research talk: Computationally efficient large-scale AI

Research talk: Towards data-efficient machine learning with meta-learning

Panel: Computer vision in the next decade: Deeper or broader

Panel: Causal ML Research at Microsoft

Masters in Financial Economics | Oxford Saïd Business School

Talk: The implicit bias of optimization algorithms in deep learning

Talk: Theoretical Aspects of Gradient Methods in Deep Learning

A law of robustness and the importance of overparametrization in deep learning

Why do people attend the Oxford Advanced Management and Leadership Programme?