ML Fundamentals

Insights into building a high-performance computing cloud platform

Continuous Deployment with Weights & Biases Automations

The responsible use of generative AI in academic information security research

Rethinking Retraining: Cost-Effective AI Solutions // Patrick Beukema // MLOps podcast #225 clip

New course with Hugging Face: Quantization in Depth 🤗

Petar Veličković - Categorical Deep Learning: An Algebraic Theory of Architectures

Beyond AGI, Can AI Help Save the Planet? // Patrick Beukema // MLOps Podcast #225

Accelerating Simulations of Multiscale Chemical Reactors | NVIDIA GTC 2024

Accelerating Drug Discovery by Combining Quantum-Based Models w/ Machine Learning | NVIDIA GTC 2024

Manual Testing vs Automation Testing | Manual vs Automation Testing | Edureka

New Way Now: Bayer AG is working to reduce radiologist burnout & improve patient diagnosis with AI

Musical performance by John Falsetto

Cheng Soon Ong - Why you Should Learn Mathematics for Machine Learning

How much training data does a neural network need?

Automation Test Engineer | Test Automation Engineer Roadmap, Skills, Tools, Salary, Jobs | Edureka

Visualizing Neural Network Internals

Top 10 Deep Learning Interview Questions And Answers | AI & Deep Learning Interview Questions

Unpacking the Essence of AI Education | Sebastian Raschka, AI Staff Educator @ Lightning AI | LWD 22

Simple ideas to improve your RAG (Stanford, Google)

Batch Normalization in neural networks - EXPLAINED!

Kernel Density Estimation : Data Science Concepts

Google Machine Learning Bootcamp Korea 2023 Recap

Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao - 668

Definition of a "bit", in information theory

Different Text Summarization Techniques Using Langchain #generativeai

INFINITE Inference Power for AI

Stanford - How Do We Make Human-Centered AI for Mental Health Prediction in Social Media Data?

Metaflow for distributed high-performance computing and large-scale AI training

Build high performance & cost-effective ML apps using Amazon SageMaker- AWS Virtual Workshop

Algorithmic Trading – Machine Learning & Quant Strategies Course with Python

Language Processing, Recommendations, System Integration // Aayush Mugdal // MLOps Podcast #211 clip

Automate & Innovate: Unlocking the Power of Model Management

Loss functions in Neural Networks - EXPLAINED!

Optimizers in Neural Networks - EXPLAINED!

The Myth of AI Breakthroughs // Jonathan Frankle // MLOps Podcast #205

Activation functions in neural networks

Backpropagation in Neural Networks - EXPLAINED!

Building your first Neural Network

Shreya Shankar: Continual training pipeline

Detecting Fraud in Financial Services Using AI Inference

Reinforcement Learning through Human Feedback - EXPLAINED! | RLHF

Scaling MLOps for Computer Vision // MLOps Mini Summit Meetup #4

Proximal Policy Optimization | ChatGPT uses this

Deep Q-Networks Explained!

Monte Carlo in Reinforcement Learning

Reinforcement Learning: on-policy vs off-policy algorithms

Q-learning - Explained!

Foundation of Q-learning | Temporal Difference Learning explained!