Foundations

ML Fundamentals

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

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ML Maths Basics
beginner
Manipulate vectors and matrices
Supervised Learning
beginner
Train decision trees, random forests, and neural nets
Unsupervised Learning
intermediate
Apply k-means and DBSCAN clustering
ML Pipelines
intermediate
Engineer features and handle missing data
Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization
ML Fundamentals
Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization
Microsoft Research Advanced 5y ago
Colab Pro Now Available In India, Brazil, France, Thailand,Japan,UK- BOON FOR Data Science Aspirants
ML Fundamentals
Colab Pro Now Available In India, Brazil, France, Thailand,Japan,UK- BOON FOR Data Science Aspirants
Krish Naik Advanced 5y ago
Oxford High Performance Leadership Programme | Ethos and Virtual Design
ML Fundamentals
Oxford High Performance Leadership Programme | Ethos and Virtual Design
Saïd Business School, University of Oxford Advanced 5y ago
Project InnerEye: Augmenting cancer radiotherapy workflows with deep learning and open source
ML Fundamentals
Project InnerEye: Augmenting cancer radiotherapy workflows with deep learning and open source
Microsoft Research Advanced 5y ago
The Discovery That Transformed Pi
ML Fundamentals
The Discovery That Transformed Pi
Veritasium Advanced 5y ago
Building World-Class NLP Models with Transformers and Hugging Face | Grandmaster Series E4
ML Fundamentals ⚡ AI Lesson
Building World-Class NLP Models with Transformers and Hugging Face | Grandmaster Series E4
NVIDIA Developer Advanced 5y ago
YOLOv3 from Scratch
ML Fundamentals
YOLOv3 from Scratch
Aladdin Persson Advanced 5y ago
Code With Me : Gibbs Sampling
ML Fundamentals
Code With Me : Gibbs Sampling
ritvikmath Advanced 5y ago
Advice on Publishing Machine Learning Papers with MLC's founder Rosanne Liu
ML Fundamentals
Advice on Publishing Machine Learning Papers with MLC's founder Rosanne Liu
Weights & Biases Advanced 5y ago
Build a 1D convolutional neural network, part 4: Training, evaluation, reporting
ML Fundamentals
Build a 1D convolutional neural network, part 4: Training, evaluation, reporting
Brandon Rohrer Advanced 5y ago
Implement 1D convolution, part 1: Convolution in Python from scratch
ML Fundamentals
Implement 1D convolution, part 1: Convolution in Python from scratch
Brandon Rohrer Advanced 5y ago
Code With Me : Decision Trees
ML Fundamentals ⚡ AI Lesson
Code With Me : Decision Trees
ritvikmath Advanced 5y ago
Call for Reproducing Papers
ML Fundamentals
Call for Reproducing Papers
Weights & Biases Advanced 5y ago
Neural Networks from Scratch - P.7 Calculating Loss with Categorical Cross-Entropy
ML Fundamentals
Neural Networks from Scratch - P.7 Calculating Loss with Categorical Cross-Entropy
sentdex Advanced 5y ago
How to Predict Which Candidate COVID-19 mRNA Vaccines Are Stable with AI | Grandmaster Series E3
ML Fundamentals
How to Predict Which Candidate COVID-19 mRNA Vaccines Are Stable with AI | Grandmaster Series E3
NVIDIA Developer Advanced 5y ago
Pixels to Concepts with Backpropagation w/ Roland Memisevic - #427
ML Fundamentals ⚡ AI Lesson
Pixels to Concepts with Backpropagation w/ Roland Memisevic - #427
The TWIML AI Podcast with Sam Charrington Advanced 5y ago
Predicting Pitch Outcomes in Major League Baseball (Student Presentation, Group 11)
ML Fundamentals
Predicting Pitch Outcomes in Major League Baseball (Student Presentation, Group 11)
Sebastian Raschka Advanced 5y ago
Machine Learning for Characterizing Climate-related Disasters (Student Presentation, Group 20)
ML Fundamentals
Machine Learning for Characterizing Climate-related Disasters (Student Presentation, Group 20)
Sebastian Raschka Advanced 5y ago
Graph Convolutional Operators in the PyTorch JIT | PyTorch Developer Day 2020
ML Fundamentals
Graph Convolutional Operators in the PyTorch JIT | PyTorch Developer Day 2020
PyTorch Advanced 5y ago
DeepSpeed | PyTorch Developer Day 2020
ML Fundamentals ⚡ AI Lesson
DeepSpeed | PyTorch Developer Day 2020
PyTorch Advanced 5y ago
Neural Networks from Scratch (NNFS) in Print!
ML Fundamentals ⚡ AI Lesson
Neural Networks from Scratch (NNFS) in Print!
sentdex Advanced 5y ago
#TWIMLfest: Live Keynote Interview with Shakir Mohamed - #418
ML Fundamentals ⚡ AI Lesson
#TWIMLfest: Live Keynote Interview with Shakir Mohamed - #418
The TWIML AI Podcast with Sam Charrington Advanced 5y ago
Can social impact survive the crisis?
ML Fundamentals
Can social impact survive the crisis?
Saïd Business School, University of Oxford Advanced 5y ago
Understanding Graph Neural Networks | Part 2/3 - GNNs and it's Variants
ML Fundamentals
Understanding Graph Neural Networks | Part 2/3 - GNNs and it's Variants
DeepFindr Advanced 5y ago
VGGNET Architecture In-depth Discussion Along With Code -Deep Learning Advanced CNN
ML Fundamentals
VGGNET Architecture In-depth Discussion Along With Code -Deep Learning Advanced CNN
Krish Naik Advanced 5y ago
Directions in ML: Taking Advantage of Randomness in Expensive Optimization Problems
ML Fundamentals ⚡ AI Lesson
Directions in ML: Taking Advantage of Randomness in Expensive Optimization Problems
Microsoft Research Advanced 5y ago
Build your own neural network, Exercise 9
ML Fundamentals
Build your own neural network, Exercise 9
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 8
ML Fundamentals
Build your own neural network, Exercise 8
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 7
ML Fundamentals
Build your own neural network, Exercise 7
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 6
ML Fundamentals
Build your own neural network, Exercise 6
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 5
ML Fundamentals
Build your own neural network, Exercise 5
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 4
ML Fundamentals ⚡ AI Lesson
Build your own neural network, Exercise 4
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 3
ML Fundamentals
Build your own neural network, Exercise 3
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 2
ML Fundamentals ⚡ AI Lesson
Build your own neural network, Exercise 2
Brandon Rohrer Advanced 5y ago
Build your own neural network, Exercise 1
ML Fundamentals ⚡ AI Lesson
Build your own neural network, Exercise 1
Brandon Rohrer Advanced 5y ago
Greg Yang on Feature Learning in Infinite-Width Networks
ML Fundamentals ⚡ AI Lesson
Greg Yang on Feature Learning in Infinite-Width Networks
Weights & Biases Advanced 5y ago
Modeling COVID Positivity Rates at U.S. College Campuses (Student Presentation, Group 16)
ML Fundamentals ⚡ AI Lesson
Modeling COVID Positivity Rates at U.S. College Campuses (Student Presentation, Group 16)
Sebastian Raschka Advanced 5y ago
Geometry-constrained Beamforming Network for end-to-end Farfield Sound Source Separation
ML Fundamentals ⚡ AI Lesson
Geometry-constrained Beamforming Network for end-to-end Farfield Sound Source Separation
Microsoft Research Advanced 5y ago
Extracting information from political ad disclosures with the DeepForm team
ML Fundamentals
Extracting information from political ad disclosures with the DeepForm team
Weights & Biases Advanced 5y ago
Look ma, no side effects! Collaborative Work on AI Safety with the SafeLife Team
ML Fundamentals ⚡ AI Lesson
Look ma, no side effects! Collaborative Work on AI Safety with the SafeLife Team
Weights & Biases Advanced 5y ago
Debug your YOLOv5 experiments with Weights & Biases
ML Fundamentals ⚡ AI Lesson
Debug your YOLOv5 experiments with Weights & Biases
Weights & Biases Advanced 5y ago
How to Perform Large-Scale Image Classification | Grandmaster Series E2
ML Fundamentals
How to Perform Large-Scale Image Classification | Grandmaster Series E2
NVIDIA Developer Advanced 5y ago
Chirag Agarwal on detecting out-of-distribution data with Variance-of-Gradient
ML Fundamentals
Chirag Agarwal on detecting out-of-distribution data with Variance-of-Gradient
Weights & Biases Advanced 5y ago
Directions in ML: AutoML & Interpretability: Powering the machine learning revolution in healthcare
ML Fundamentals
Directions in ML: AutoML & Interpretability: Powering the machine learning revolution in healthcare
Microsoft Research Advanced 5y ago
Granger Causality in Python : Data Science Code
ML Fundamentals ⚡ AI Lesson
Granger Causality in Python : Data Science Code
ritvikmath Advanced 5y ago
Alexnet Architecture In-depth-Discussion Along With Code-Deep Learning Advanced CNN
ML Fundamentals
Alexnet Architecture In-depth-Discussion Along With Code-Deep Learning Advanced CNN
Krish Naik Advanced 5y ago
Making cryptography accessible, efficient, and scalable with Dr. Divya Gupta and Dr. Rahul Sharma
ML Fundamentals
Making cryptography accessible, efficient, and scalable with Dr. Divya Gupta and Dr. Rahul Sharma
Microsoft Research Advanced 5y ago
What Kind of Computation is Human Cognition? A Brief History of Thought (Episode 1/2)
ML Fundamentals
What Kind of Computation is Human Cognition? A Brief History of Thought (Episode 1/2)
Microsoft Research Advanced 5y ago
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Building and Training Neural Networks with PyTorch
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Sequence Modeling, Transformers, and Transfer Learning
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Probabilistic Graphical Models 3: Learning
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Probabilistic Graphical Models 3: Learning
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GenAI for Risk Managers: Advanced Risk Analysis Techniques
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GenAI for Risk Managers: Advanced Risk Analysis Techniques
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