ML Fundamentals

Text Classification: Handling 1000+ Classes with Generative AI | Amazon Web Services

Inception Net - Explained! (with code)

Stanford Webinar - From Pixels to Human Impact: Unlocking Real-World Value with Computer Vision

Pointwise Convolutions - EXPLAINED (with code)

Future Climate Innovators Summer School

Will AI Replace Your Job? Here’s the Truth #FutureOfWork #AIJobs #Workplace #Automation #AIFuture

How you can SAVE A LOT OF TIME with Pre-trained models

Why synthetic data isn’t enough

Machine Learning models are HERE TO STAY

Eco-aware GNN Recommenders

Broadridge Forecasts the Future of Asset Management with AWS | Amazon Web Services

NIMCET 2026 Preparation | NIMCET PYQ | NIMCET Free PYQ Series | NIMCET Big Announcement

Tom Jacobs Weight Decay Controls Implicit Regularization Insights on Generalization and Sparsity

Mufan Li - Introduction to Neural Network Scaling Limits

The Tech Job Market Divide: WTF is Happening?

Reinforcement learning with Unitree G1 humanoid - Dev w/ G1 P.5

Structuring a modern AI team — Denys Linkov, Wisedocs

Akiko Funaki | Advanced Management Leadership Programme

Lecture 5: Sums

2 Game-Changing Tips for Virtual Presentations That Actually Work (Part 1/4)

Sponsored by: SAP | SAP and Databricks Open a Bold New Era of Data and AI​

Databricks as the Backbone of MLOps: From Orchestration to Inference

Stanford AA222 I Engineering Design Optimization | Spring 2025 | Disciplined Convex Programming

no distributed training

The State of AI Powered Search and Retrieval — Frank Liu, MongoDB (prev Voyage AI)

Deconvolution - what do networks learn? (visualization + code)

The AI REVOLUTION has TAKEN US by STORM

The SURPRISING POWER of PRIVATE DATA Revealed

R-CNN - Explained!

Region Proposals - Explained!

Image segmentation - Explained!

How was object detection done before neural networks?

Why neural networks are so deep? (AlexNet - Explained)

Visualizing convolution networks

#313 Better Predictive Models with Graph Transformers | Jure Leskovec, Professor at Stanford

Why convolution networks work so well (on images)

How Natera scales genomics with Amazon SageMaker Catalog | Amazon Web Services

Configure & use Amazon FSx for Lustre with Amazon EKS Pods | Amazon Web Services

Convolution Network back propagation by hand | the math you should know!

Arthur Douillard - Distributed Training in Machine Learning

Revolutionizing Neural Network Training: Tony S.F. Explains Optimization with LMO

TAO and Reinforcement Learning: Building AI With the Data You Have

Future-Ready Data at Scale: How Shutterfly Modernized for GenAI-Driven Personalization

Webinar: Alumni in Action: Oxford Insights and Sustainability Leadership

Tony Silveti Falls - Training neural networks at any scale

Back propagation by hand | the math you should know

Andrej Jovanovic -Communication efficient training for foundation models through federated learning

How AWS machine learning supports Scuderia Ferrari HP pit stops | Amazon Web Services