📐 ML Fundamentals

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

ML Fundamentals

In this Mass Layoff Becoming Recession proof-Is it Possible??

Krish Naik Advanced 2y ago

ML Fundamentals

I waterproofed myself with aerogel!

Veritasium Advanced 2y ago

ML Fundamentals

Kernel Density Estimation : Data Science Concepts

ritvikmath Advanced 2y ago

ML Fundamentals

Loss functions in Neural Networks - EXPLAINED!

CodeEmporium Advanced 2y ago

ML Fundamentals

Google Machine Learning Bootcamp Korea 2023 Recap

Google for Developers Advanced 2y ago

ML Fundamentals

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

The TWIML AI Podcast with Sam Charrington Advanced 2y ago

ML Fundamentals

Optimizers in Neural Networks - EXPLAINED!

CodeEmporium Advanced 2y ago

ML Fundamentals

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

MLOps.community Advanced 2y ago

ML Fundamentals

Definition of a "bit", in information theory

3Blue1Brown Advanced 2y ago

ML Fundamentals

The limit of limiting arguments

3Blue1Brown Advanced 2y ago

ML Fundamentals

Different Text Summarization Techniques Using Langchain #generativeai

Krish Naik Advanced 2y ago

ML Fundamentals

INFINITE Inference Power for AI

sentdex Advanced 2y ago

ML Fundamentals

Shreya Shankar: Continual training pipeline

Weights & Biases Advanced 2y ago

ML Fundamentals

Detecting Fraud in Financial Services Using AI Inference

NVIDIA Developer Advanced 2y ago

ML Fundamentals

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

MLOps.community Advanced 2y ago

ML Fundamentals

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

Stanford Online Advanced 2y ago

ML Fundamentals

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

Outerbounds Advanced 2y ago

ML Fundamentals

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

AWS Developers Advanced 2y ago

ML Fundamentals

Algorithmic Trading – Machine Learning & Quant Strategies Course with Python

freeCodeCamp.org Advanced 2y ago

ML Fundamentals

Lightning Talk: Uplink Interference Optimizer, How to Optimize a Cellular Network...- Oscar Gonzalez

PyTorch Advanced 2y ago

ML Fundamentals

Why Deep Networks and Brains Learn Similar Features with Sophia Sanborn - 644

The TWIML AI Podcast with Sam Charrington Advanced 2y ago

ML Fundamentals

Stanford XCS224U I Analysis NLU, Pt 4: Casual Abstraction & Interchange Intervention Training (IIT)

Stanford Online Advanced 2y ago

ML Fundamentals

How to Hack an AI

SANS Institute Advanced 2y ago

ML Fundamentals

The secret to Accelerate #ML and #GenerativeAI: ML Developer Tools from Weights & Biases.

Google Cloud Advanced 2y ago

ML Fundamentals

Day in the life of Oxford Advanced Management & Leadership Programme - June 2023

Saïd Business School, University of Oxford Advanced 2y ago

ML Fundamentals

In-Context Learning Over Graphs for LLMs: PRODIGY (Stanford)

Discover AI Advanced 2y ago

ML Fundamentals

PyTorch New York Meetup - June 2023

PyTorch Advanced 2y ago

ML Fundamentals

Hugging Face: Fine-Tune NLP Pipeline for Question Answering | Transformers & Attention Mechanism

Analytics Vidhya Advanced 2y ago

ML Fundamentals

Activation functions in neural networks

CodeEmporium Advanced 2y ago

ML Fundamentals

Backpropagation in Neural Networks - EXPLAINED!

CodeEmporium Advanced 2y ago

ML Fundamentals

Building your first Neural Network

CodeEmporium Advanced 2y ago

ML Fundamentals

Reinforcement Learning through Human Feedback - EXPLAINED! | RLHF

CodeEmporium Advanced 2y ago

ML Fundamentals

Proximal Policy Optimization | ChatGPT uses this

CodeEmporium Advanced 2y ago

ML Fundamentals

Deep Q-Networks Explained!

CodeEmporium Advanced 2y ago

ML Fundamentals

Monte Carlo in Reinforcement Learning

CodeEmporium Advanced 2y ago

ML Fundamentals

Reinforcement Learning: on-policy vs off-policy algorithms

CodeEmporium Advanced 2y ago

ML Fundamentals

Q-learning - Explained!

CodeEmporium Advanced 2y ago

ML Fundamentals

Foundation of Q-learning | Temporal Difference Learning explained!

CodeEmporium Advanced 2y ago

ML Fundamentals

Bellman Equation - Explained!

CodeEmporium Advanced 2y ago

ML Fundamentals

How to solve problems with Reinforcement Learning | Markov Decision Process

CodeEmporium Advanced 2y ago

ML Fundamentals

Multi Armed Bandits - Reinforcement Learning Explained!

CodeEmporium Advanced 2y ago

ML Fundamentals

Elements of Reinforcement Learning

CodeEmporium Advanced 2y ago

ML Fundamentals

ChatGPT: Zero to Hero

CodeEmporium Advanced 2y ago

ML Fundamentals

Sentence Embeddings - EXPLAINED!

CodeEmporium Advanced 2y ago

ML Fundamentals

Designing Human in the Loop Experiences for LLMs // Alberto Rizzoli // LLMs in Prod Con Part 2

MLOps.community Advanced 2y ago

ML Fundamentals

A pretty reason why Gaussian + Gaussian = Gaussian

3Blue1Brown Advanced 2y ago

ML Fundamentals

Stanford Seminar - Control-Oriented Learning for Dynamical Systems

Stanford Online Advanced 2y ago

ML Fundamentals

Word2Vec, GloVe, FastText- EXPLAINED!

CodeEmporium Advanced 2y ago

📚 Coursera Courses Opens on Coursera · Free to audit

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Self-paced

Getting started with TensorFlow 2

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ML Pipelines on Google Cloud - Português

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Self-paced

Building a Machine Learning Ready Organization

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Self-paced

Tune HNSW

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Deep learning in Electronic Health Records - CDSS 2

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Deep Learning with PyTorch : GradCAM

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Data Science Fundamentals Part 2: Unit 3

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📚 Coursera Course ↗

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Natural Language Processing with Classification and Vector Spaces

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DataPrep for H2O Driverless AI

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Self-paced

Master Machine Learning with TensorFlow: Basics to Advanced

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📚 Coursera Course ↗

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Machine Learning and Emerging Technologies in Cybersecurity

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📚 Coursera Course ↗

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Deep Learning with PyTorch : Generative Adversarial Network

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Prediction and Control with Function Approximation

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Practical MATLAB Skills

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Calculus for Engineers

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Foundations of Data Science and Machine Learning with Python

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Deep Learning with ANN in Python: Build & Optimize

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Automate, Optimize, and Monitor ML Models

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