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
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Powered by PyTorch at F8 2019
ML Fundamentals
Powered by PyTorch at F8 2019
PyTorch Beginner 6y ago
Introduction to Machine Learning for Developers at F8 2019
ML Fundamentals
Introduction to Machine Learning for Developers at F8 2019
PyTorch Beginner 6y ago
Designing a Machine Learning Project with Neal Khosla (2019)
ML Fundamentals
Designing a Machine Learning Project with Neal Khosla (2019)
Weights & Biases Beginner 6y ago
How a Biologist became a Data Scientist
ML Fundamentals
How a Biologist became a Data Scientist
Data Professor Beginner 6y ago
Tutorial 21- What is Convolution operation in CNN?
ML Fundamentals
Tutorial 21- What is Convolution operation in CNN?
Krish Naik Beginner 6y ago
Tutorial 20- Convolution Neural Network vs Human Brain
ML Fundamentals
Tutorial 20- Convolution Neural Network vs Human Brain
Krish Naik Beginner 6y ago
These books will help you learn machine learning
ML Fundamentals ⚡ AI Lesson
These books will help you learn machine learning
Daniel Bourke Beginner 6y ago
Supervised Learning: Crash Course AI #2
ML Fundamentals
Supervised Learning: Crash Course AI #2
CrashCourse Beginner 6y ago
Inside TensorFlow: tf.distribute.Strategy
ML Fundamentals ⚡ AI Lesson
Inside TensorFlow: tf.distribute.Strategy
TensorFlow Intermediate 6y ago
Model Understanding and Business Reality (TensorFlow Extended)
ML Fundamentals ⚡ AI Lesson
Model Understanding and Business Reality (TensorFlow Extended)
TensorFlow Beginner 6y ago
Tesla is Going to Win Level 5 - George Hotz | AI Podcast Clips
ML Fundamentals ⚡ AI Lesson
Tesla is Going to Win Level 5 - George Hotz | AI Podcast Clips
Lex Fridman Beginner 6y ago
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
ML Fundamentals
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
Yannic Kilcher Intermediate 6y ago
The Problem with Black Boxes with Cynthia Rudin - TWIML Talk #290
ML Fundamentals ⚡ AI Lesson
The Problem with Black Boxes with Cynthia Rudin - TWIML Talk #290
The TWIML AI Podcast with Sam Charrington Beginner 6y ago
Siamese Neural Networks
ML Fundamentals
Siamese Neural Networks
Connor Shorten Advanced 6y ago
NASA Chief Scientist | Dr. Jim Green | Talks at Google
ML Fundamentals
NASA Chief Scientist | Dr. Jim Green | Talks at Google
Talks at Google Beginner 6y ago
Manifold Mixup: Better Representations by Interpolating Hidden States
ML Fundamentals
Manifold Mixup: Better Representations by Interpolating Hidden States
Yannic Kilcher Beginner 6y ago
Multi Programming - Computerphile
ML Fundamentals ⚡ AI Lesson
Multi Programming - Computerphile
Computerphile Intermediate 6y ago
Troubleshooting and Iterating ML Models with Lee Redden (2019)
ML Fundamentals
Troubleshooting and Iterating ML Models with Lee Redden (2019)
Weights & Biases Beginner 6y ago
University of Illinois Master of Computer Science (& MCS-DS) - a top-ranked degree
ML Fundamentals
University of Illinois Master of Computer Science (& MCS-DS) - a top-ranked degree
Coursera Beginner 6y ago
Automated ML for RNA Design with Danny Stoll - TWIML Talk #288
ML Fundamentals ⚡ AI Lesson
Automated ML for RNA Design with Danny Stoll - TWIML Talk #288
The TWIML AI Podcast with Sam Charrington Advanced 6y ago
PyTorch 1.2 and PyTorch Hub: A Quick Introduction by Soumith Chintala and Ailing Zhang
ML Fundamentals
PyTorch 1.2 and PyTorch Hub: A Quick Introduction by Soumith Chintala and Ailing Zhang
PyTorch Beginner 6y ago
Tips and Tricks on Hacking with PyTorch: A Quick Tutorial by Brad Heintz
ML Fundamentals
Tips and Tricks on Hacking with PyTorch: A Quick Tutorial by Brad Heintz
PyTorch Beginner 6y ago
How To Handle Missing Values in Categorical Features
ML Fundamentals
How To Handle Missing Values in Categorical Features
Krish Naik Intermediate 6y ago
What is PyTorch?
ML Fundamentals
What is PyTorch?
PyTorch Beginner 6y ago
Cosine Similarity and Cosine Distance
ML Fundamentals
Cosine Similarity and Cosine Distance
Krish Naik Intermediate 6y ago
Euclidean Distance and Manhattan Distance
ML Fundamentals
Euclidean Distance and Manhattan Distance
Krish Naik Intermediate 6y ago
Why Do I Teach? Motivations
ML Fundamentals
Why Do I Teach? Motivations
Krish Naik Intermediate 6y ago
Data Engineer vs Data Analyst vs Data Scientist
ML Fundamentals
Data Engineer vs Data Analyst vs Data Scientist
Krish Naik Intermediate 6y ago
What Do A Data Scientist Do?
ML Fundamentals
What Do A Data Scientist Do?
Krish Naik Intermediate 6y ago
Why Do We Need to Perform Feature Scaling?
ML Fundamentals
Why Do We Need to Perform Feature Scaling?
Krish Naik Intermediate 6y ago
Different Types of Feature Engineering Encoding Techniques
ML Fundamentals
Different Types of Feature Engineering Encoding Techniques
Krish Naik Intermediate 6y ago
How to Crack Data Science Interviews- Motivations
ML Fundamentals
How to Crack Data Science Interviews- Motivations
Krish Naik Intermediate 6y ago
What should be your Salary Expectation as a Data Scientist?
ML Fundamentals
What should be your Salary Expectation as a Data Scientist?
Krish Naik Intermediate 6y ago
Step By Step Transition Towards Data Science
ML Fundamentals
Step By Step Transition Towards Data Science
Krish Naik Intermediate 6y ago
Tutorial 37: Entropy In Decision Tree Intuition
ML Fundamentals
Tutorial 37: Entropy In Decision Tree Intuition
Krish Naik Beginner 6y ago
Feature Engineering-How to Perform One Hot Encoding for Multi Categorical Variables
ML Fundamentals
Feature Engineering-How to Perform One Hot Encoding for Multi Categorical Variables
Krish Naik Intermediate 6y ago
Complete Life Cycle of a Data Science Project
ML Fundamentals
Complete Life Cycle of a Data Science Project
Krish Naik Intermediate 6y ago
My Path on Becoming a Data Scientist- Motivation
ML Fundamentals
My Path on Becoming a Data Scientist- Motivation
Krish Naik Intermediate 6y ago
Train Test Split vs K Fold vs Stratified K fold Cross Validation
ML Fundamentals
Train Test Split vs K Fold vs Stratified K fold Cross Validation
Krish Naik Intermediate 6y ago
What is Cross Validation and its types?
ML Fundamentals
What is Cross Validation and its types?
Krish Naik Beginner 6y ago
Tutorial 19- Training Artificial Neural Network using Google Colab GPU
ML Fundamentals
Tutorial 19- Training Artificial Neural Network using Google Colab GPU
Krish Naik Beginner 6y ago
Applied Deep Learning - Troubleshooting and Debugging with Josh Tobin (2019)
ML Fundamentals
Applied Deep Learning - Troubleshooting and Debugging with Josh Tobin (2019)
Weights & Biases Beginner 6y ago
Distributed Processing and Components (TensorFlow Extended)
ML Fundamentals ⚡ AI Lesson
Distributed Processing and Components (TensorFlow Extended)
TensorFlow Beginner 6y ago
Tutorial 18- Hyper parameter Tuning To Decide Number of Hidden Layers in Neural Network
ML Fundamentals
Tutorial 18- Hyper parameter Tuning To Decide Number of Hidden Layers in Neural Network
Krish Naik Beginner 6y ago
Tutorial 17- Create Artificial Neural Network using Weight Initialization Tricks
ML Fundamentals
Tutorial 17- Create Artificial Neural Network using Weight Initialization Tricks
Krish Naik Beginner 6y ago
TWiML x Fast.ai Deep Learning Part 2 Study Group - Lesson 5
ML Fundamentals ⚡ AI Lesson
TWiML x Fast.ai Deep Learning Part 2 Study Group - Lesson 5
The TWIML AI Podcast with Sam Charrington Beginner 6y ago
Reconciling modern machine learning and the bias-variance trade-off
ML Fundamentals ⚡ AI Lesson
Reconciling modern machine learning and the bias-variance trade-off
Yannic Kilcher Advanced 6y ago
Tutorial 4- Book Recommendation using Collaborative Filtering
ML Fundamentals
Tutorial 4- Book Recommendation using Collaborative Filtering
Krish Naik Beginner 6y ago
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Learning TensorFlow: the Hello World of Machine Learning
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Introduction to Advanced Calculus
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