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
Every model I build has to answer 1 simple question | Airbnb Machine Learning Project Part 5
ML Fundamentals
Every model I build has to answer 1 simple question | Airbnb Machine Learning Project Part 5
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ML Fundamentals
My Laptop Lenovo Legion Y 540 Unboxing For Deep Learning! Important Message At The Last
Krish Naik Beginner 6y ago
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ML Fundamentals
Deep Learning for Coders Study Group - Session #10
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ML Fundamentals
Lecture 2- Competitive Programming- Problem Statement 1
Krish Naik Intermediate 6y ago
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ML Fundamentals
R Tutorial: Handling missing data
DataCamp Beginner 6y ago
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ML Fundamentals
R Tutorial: Data normalization
DataCamp Beginner 6y ago
The Best Free Data Science Courses Nobody is Talking About
ML Fundamentals
The Best Free Data Science Courses Nobody is Talking About
Ken Jee Beginner 6y ago
1D convolution for neural networks, part 9: Stride
ML Fundamentals
1D convolution for neural networks, part 9: Stride
Brandon Rohrer Intermediate 6y ago
1D convolution for neural networks, part 8: Padding
ML Fundamentals
1D convolution for neural networks, part 8: Padding
Brandon Rohrer Intermediate 6y ago
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ML Fundamentals
Comparing AGI and Traditional AI: Now and Beyond
What's AI by Louis-François Bouchard Beginner 6y ago
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ML Fundamentals
What is NLP ? | Introduction to Natural Language Processing for Beginners | Machine Learning 12
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ML Fundamentals
Secrets of a Kaggle Grandmaster with David Odaibo - #354
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ML Fundamentals
Illinois Online Master of Computer Science (MCS) and MCS in Data Science Admissions Webinar
Coursera Intermediate 6y ago
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ML Fundamentals
Coding Trees in Python - Computerphile
Computerphile Intermediate 6y ago
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ML Fundamentals
Machine Learning Bootcamp Jakarta 2019
Google for Developers Beginner 6y ago
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ML Fundamentals
Python Programmer Bootcamp: NEW Python Programming Course
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Consciousness is an Explanation of What Already Has Been Computed (John Hopfield) | AI Podcast Clips
ML Fundamentals
Consciousness is an Explanation of What Already Has Been Computed (John Hopfield) | AI Podcast Clips
Lex Fridman Beginner 6y ago
John Hopfield: Physics View of the Mind and Neurobiology | Lex Fridman Podcast #76
ML Fundamentals
John Hopfield: Physics View of the Mind and Neurobiology | Lex Fridman Podcast #76
Lex Fridman Beginner 6y ago
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ML Fundamentals
This Neural Network Creates 3D Objects From Your Photos
Two Minute Papers Beginner 6y ago
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ML Fundamentals
The Problem with Data Science
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ML Fundamentals
RegEx Roman Numerals - Computerphile
Computerphile Intermediate 6y ago
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ML Fundamentals
Getting Started with Azure Machine Learning Studio
The AI Guy Beginner 6y ago
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ML Fundamentals
Episode 4: Simple and Basic Binary Classification Metrics
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ML Fundamentals
Heroes of Deep Learning: Yann LeCun and Ruslan Salakhutdinov on Getting Started
DeepLearningAI Beginner 6y ago
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ML Fundamentals
Deep Learning for Symbolic Mathematics
Yannic Kilcher Advanced 6y ago
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ML Fundamentals
The Future Will Be Genetically Engineered
a16z Beginner 6y ago
Lecture 1-  Data Structures And Analysis Of Algorithms
ML Fundamentals
Lecture 1- Data Structures And Analysis Of Algorithms
Krish Naik Intermediate 6y ago
1D convolution for neural networks, part 7: Weight gradient
ML Fundamentals
1D convolution for neural networks, part 7: Weight gradient
Brandon Rohrer Intermediate 6y ago
1D convolution for neural networks, part 6: Input gradient
ML Fundamentals
1D convolution for neural networks, part 6: Input gradient
Brandon Rohrer Intermediate 6y ago
1D convolution for neural networks, part 5: Backpropagation
ML Fundamentals
1D convolution for neural networks, part 5: Backpropagation
Brandon Rohrer Intermediate 6y ago
1D convolution for neural networks, part 4: Convolution equation
ML Fundamentals
1D convolution for neural networks, part 4: Convolution equation
Brandon Rohrer Intermediate 6y ago
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ML Fundamentals
1D convolution for neural networks, part 3: Sliding dot product equations longhand
Brandon Rohrer Intermediate 6y ago
1D convolution for neural networks, part 2: Convolution copies the kernel
ML Fundamentals
1D convolution for neural networks, part 2: Convolution copies the kernel
Brandon Rohrer Intermediate 6y ago
1D convolution for neural networks, part 1: Sliding dot product
ML Fundamentals
1D convolution for neural networks, part 1: Sliding dot product
Brandon Rohrer Intermediate 6y ago
R Tutorial: Model Validation, Model Fit, and Prediction
ML Fundamentals
R Tutorial: Model Validation, Model Fit, and Prediction
DataCamp Beginner 6y ago
Live Q&A Data Science
ML Fundamentals
Live Q&A Data Science
Krish Naik Intermediate 6y ago
Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2
ML Fundamentals
Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2
Krish Naik Beginner 6y ago
Python Tutorial: Decision-Tree for Regression
ML Fundamentals
Python Tutorial: Decision-Tree for Regression
DataCamp Beginner 6y ago
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ML Fundamentals
Managing Real-Life Data Science Projects with Metaflow - Democast #3
The TWIML AI Podcast with Sam Charrington Intermediate 6y ago
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ML Fundamentals
Custom Ensemble Approach To Solve Machine Learning Problems
Krish Naik Beginner 6y ago
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ML Fundamentals
R Tutorial: Bivariate graphics
DataCamp Beginner 6y ago
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ML Fundamentals
Python Tutorial: Machine Learning modeling steps
DataCamp Beginner 6y ago
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ML Fundamentals
Why And How Did I Get Into Data Science? Sharing My Data Science Experience In 20 min
Krish Naik Intermediate 6y ago
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ML Fundamentals
What is Backpropagation | Artificial Intelligence & Machine Learning Basics for Beginners 11
What's AI by Louis-François Bouchard Beginner 6y ago
Metric Elicitation and Robust Distributed Learning with Sanmi Koyejo - #352
ML Fundamentals
Metric Elicitation and Robust Distributed Learning with Sanmi Koyejo - #352
The TWIML AI Podcast with Sam Charrington Beginner 6y ago
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ML Fundamentals
Follow These Steps To Be Successful In IT Industries
Krish Naik Intermediate 6y ago
What is Statistics? (Michael I. Jordan) | AI Podcast Clips
ML Fundamentals
What is Statistics? (Michael I. Jordan) | AI Podcast Clips
Lex Fridman Beginner 6y ago
High-Dimensional Robust Statistics with Ilias Diakonikolas - #351
ML Fundamentals
High-Dimensional Robust Statistics with Ilias Diakonikolas - #351
The TWIML AI Podcast with Sam Charrington Beginner 6y ago
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