Foundations

ML Fundamentals

Neural networks, backpropagation, gradient descent โ€” the maths behind AI

11,232
lessons
Skills in this topic
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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
Failing Jump Rope + Neuroplasticity with Mandy ๐Ÿ‘ฝ๐ŸŒŽ
ML Fundamentals
Failing Jump Rope + Neuroplasticity with Mandy ๐Ÿ‘ฝ๐ŸŒŽ
deeplizard Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Counting I 2022 I Lecture 29
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Counting I 2022 I Lecture 29
Stanford Online Beginner 2y ago
Sayak Paul - Getting started with community contributions, diffusion models, and more
ML Fundamentals โšก AI Lesson
Sayak Paul - Getting started with community contributions, diffusion models, and more
TensorFlow Beginner 2y ago
Insights on Real-Time ML and Its Impact on Traffic Predictions // Ketan Umare // Podcast clip #183
ML Fundamentals
Insights on Real-Time ML and Its Impact on Traffic Predictions // Ketan Umare // Podcast clip #183
MLOps.community Beginner 2y ago
Why LSTM over RNNs? #deeplearning #machinelearning
ML Fundamentals โšก AI Lesson
Why LSTM over RNNs? #deeplearning #machinelearning
CodeEmporium Beginner 2y ago
Deep Learning for Newbies: Supervised or Unsupervised? ๐Ÿ›ค๏ธ๐Ÿง  - Topic 013 #ai #ml
ML Fundamentals โšก AI Lesson
Deep Learning for Newbies: Supervised or Unsupervised? ๐Ÿ›ค๏ธ๐Ÿง  - Topic 013 #ai #ml
deeplizard Beginner 2y ago
Telematics with Metaflow: How Nirvana Insurance built a large-scale Risk Estimation platform
ML Fundamentals โšก AI Lesson
Telematics with Metaflow: How Nirvana Insurance built a large-scale Risk Estimation platform
Outerbounds Beginner 2y ago
AI Olympics - 100m Race #ai #deeplearning
ML Fundamentals
AI Olympics - 100m Race #ai #deeplearning
AI Warehouse Beginner 2y ago
Highest paying jobs that DONโ€™T require a degree!
ML Fundamentals
Highest paying jobs that DONโ€™T require a degree!
Coursera Beginner 2y ago
Lightning Talk: Triton Compiler - Thomas Raoux, OpenAI
ML Fundamentals
Lightning Talk: Triton Compiler - Thomas Raoux, OpenAI
PyTorch Beginner 2y ago
Lightning Talk: Streamlining Model Export with the New ONNX Exporter - Maanav Dalal & Aaron Bockover
ML Fundamentals โšก AI Lesson
Lightning Talk: Streamlining Model Export with the New ONNX Exporter - Maanav Dalal & Aaron Bockover
PyTorch Beginner 2y ago
Many People Have Forgetten This!
ML Fundamentals
Many People Have Forgetten This!
Krish Naik Beginner 2y ago
Artificial Neural Network Tutorial | Deep Learning With Neural Networks | Edureka Rewind
ML Fundamentals
Artificial Neural Network Tutorial | Deep Learning With Neural Networks | Edureka Rewind
edureka! Beginner 2y ago
This is the Math You Need to Master Reinforcement Learning
ML Fundamentals
This is the Math You Need to Master Reinforcement Learning
ritvikmath Beginner 2y ago
Lecture 1 Part 1: Introduction and Motivation
ML Fundamentals
Lecture 1 Part 1: Introduction and Motivation
MIT OpenCourseWare Beginner 2y ago
Lecture 8 Part 1: Derivatives of Eigenproblems
ML Fundamentals
Lecture 8 Part 1: Derivatives of Eigenproblems
MIT OpenCourseWare Beginner 2y ago
Transformers Neural Networks | NLP with Deep Learning | Deep Learning  Tutorial | Edureka Live
ML Fundamentals
Transformers Neural Networks | NLP with Deep Learning | Deep Learning Tutorial | Edureka Live
edureka! Beginner 2y ago
Why Decision Tree is called Decision Tree? ๐ŸŒฒ๐ŸŽ„ Explained in 60 Seconds
ML Fundamentals
Why Decision Tree is called Decision Tree? ๐ŸŒฒ๐ŸŽ„ Explained in 60 Seconds
Analytics Vidhya Beginner 2y ago
๐ŸคซThe secret about online degrees that no one is talking about
ML Fundamentals
๐ŸคซThe secret about online degrees that no one is talking about
Coursera Beginner 2y ago
Complete Data Science Resume Repository And Guide For ML engineers, Data analyst With 20+ Resumes
ML Fundamentals
Complete Data Science Resume Repository And Guide For ML engineers, Data analyst With 20+ Resumes
Krish Naik Beginner 2y ago
Adversarial Attacks and Defenses. The Dimpled Manifold Hypothesis. David Stutz from DeepMind #HLF23
ML Fundamentals โšก AI Lesson
Adversarial Attacks and Defenses. The Dimpled Manifold Hypothesis. David Stutz from DeepMind #HLF23
AI Coffee Break with Letitia Beginner 2y ago
The AI World Cup | Scoring Goals with Artificial Intelligence | Abhay Sharma
ML Fundamentals
The AI World Cup | Scoring Goals with Artificial Intelligence | Abhay Sharma
GeeksforGeeks Beginner 2y ago
Maximizing the Potential of Deep Learning in Tabular Data Analysis // Sachin Abeywardana //#180 clip
ML Fundamentals
Maximizing the Potential of Deep Learning in Tabular Data Analysis // Sachin Abeywardana //#180 clip
MLOps.community Beginner 2y ago
Trying Beaded Jump Rope with Mandy + Harvestmen ๐Ÿ•ท๏ธ
ML Fundamentals
Trying Beaded Jump Rope with Mandy + Harvestmen ๐Ÿ•ท๏ธ
deeplizard Beginner 2y ago
Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch...- George Stefanakis & Dheeraj Peri
ML Fundamentals โšก AI Lesson
Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch...- George Stefanakis & Dheeraj Peri
PyTorch Beginner 2y ago
Keynote: Intel and PyTorch: Enabling AI Everywhere with Ubiquitous Hardware and Open... - Fan Zhao
ML Fundamentals โšก AI Lesson
Keynote: Intel and PyTorch: Enabling AI Everywhere with Ubiquitous Hardware and Open... - Fan Zhao
PyTorch Beginner 2y ago
Lightning Talk: A Novel Domain Generalization Technique for Medical Imaging Using... - Dinkar Juyal
ML Fundamentals โšก AI Lesson
Lightning Talk: A Novel Domain Generalization Technique for Medical Imaging Using... - Dinkar Juyal
PyTorch Beginner 2y ago
Lightning Talk: Seismic Data to Subsurface Models with OpenFWI - Benjamin Consolvo, Intel
ML Fundamentals โšก AI Lesson
Lightning Talk: Seismic Data to Subsurface Models with OpenFWI - Benjamin Consolvo, Intel
PyTorch Beginner 2y ago
Lightning Talk: Energy-Efficient Deep Learning with PyTorch and Zeus - Jae-Won Chung
ML Fundamentals
Lightning Talk: Energy-Efficient Deep Learning with PyTorch and Zeus - Jae-Won Chung
PyTorch Beginner 2y ago
Lecture 3 Part 1: Kronecker Products and Jacobians
ML Fundamentals
Lecture 3 Part 1: Kronecker Products and Jacobians
MIT OpenCourseWare Beginner 2y ago
Lecture 3 Part 2: Finite-Difference Approximations
ML Fundamentals
Lecture 3 Part 2: Finite-Difference Approximations
MIT OpenCourseWare Beginner 2y ago
Lecture 2 Part 1: Derivatives in Higher Dimensions: Jacobians and Matrix Functions
ML Fundamentals โšก AI Lesson
Lecture 2 Part 1: Derivatives in Higher Dimensions: Jacobians and Matrix Functions
MIT OpenCourseWare Beginner 2y ago
Lecture 4 Part 2: Nonlinear Root Finding, Optimization, and Adjoint Gradient Methods
ML Fundamentals
Lecture 4 Part 2: Nonlinear Root Finding, Optimization, and Adjoint Gradient Methods
MIT OpenCourseWare Beginner 2y ago
Lecture 7 Part 2: Second Derivatives, Bilinear Forms, and Hessian Matrices
ML Fundamentals
Lecture 7 Part 2: Second Derivatives, Bilinear Forms, and Hessian Matrices
MIT OpenCourseWare Beginner 2y ago
Lecture 4 Part 1: Gradients and Inner Products in Other Vector Spaces
ML Fundamentals โšก AI Lesson
Lecture 4 Part 1: Gradients and Inner Products in Other Vector Spaces
MIT OpenCourseWare Beginner 2y ago
Lecture 2 Part 2: Vectorization of Matrix Functions
ML Fundamentals โšก AI Lesson
Lecture 2 Part 2: Vectorization of Matrix Functions
MIT OpenCourseWare Beginner 2y ago
Lecture 1 Part 2: Derivatives as Linear Operators
ML Fundamentals
Lecture 1 Part 2: Derivatives as Linear Operators
MIT OpenCourseWare Beginner 2y ago
Lecture 8 Part 2: Automatic Differentiation on Computational Graphs
ML Fundamentals
Lecture 8 Part 2: Automatic Differentiation on Computational Graphs
MIT OpenCourseWare Beginner 2y ago
Lecture 7 Part 1: Derivatives of Random Functions
ML Fundamentals
Lecture 7 Part 1: Derivatives of Random Functions
MIT OpenCourseWare Beginner 2y ago
Lecture 6 Part 1: Adjoint Differentiation of ODE Solutions
ML Fundamentals โšก AI Lesson
Lecture 6 Part 1: Adjoint Differentiation of ODE Solutions
MIT OpenCourseWare Beginner 2y ago
Lecture 6 Part 2: Calculus of Variations and Gradients of Functionals
ML Fundamentals
Lecture 6 Part 2: Calculus of Variations and Gradients of Functionals
MIT OpenCourseWare Beginner 2y ago
Supervised Learning in Neural Networks: An Explainer ๐Ÿง ๐Ÿ” - Topic 012 #ai #ml
ML Fundamentals โšก AI Lesson
Supervised Learning in Neural Networks: An Explainer ๐Ÿง ๐Ÿ” - Topic 012 #ai #ml
deeplizard Beginner 2y ago
How Many Pushups to Failure?? with Mandy ๐Ÿฅต
ML Fundamentals
How Many Pushups to Failure?? with Mandy ๐Ÿฅต
deeplizard Beginner 2y ago
How Neural Networks Learn: A Workplace Analogy ๐Ÿข๐Ÿง  - Topic 011 #ai #ml
ML Fundamentals โšก AI Lesson
How Neural Networks Learn: A Workplace Analogy ๐Ÿข๐Ÿง  - Topic 011 #ai #ml
deeplizard Beginner 2y ago
Most Intense Lift for Chest with Mandy + ๐Ÿบ๐Ÿ•ท๏ธ
ML Fundamentals
Most Intense Lift for Chest with Mandy + ๐Ÿบ๐Ÿ•ท๏ธ
deeplizard Beginner 2y ago
Types Of Artificial Intelligence | Artificial Intelligence Explained | What is AI? | Edureka
ML Fundamentals
Types Of Artificial Intelligence | Artificial Intelligence Explained | What is AI? | Edureka
edureka! Beginner 2y ago
Deep Learning 101: Training, Goals, and Predictions Explained ๐Ÿš€๐Ÿ“˜ - Topic 010 #ai #ml
ML Fundamentals โšก AI Lesson
Deep Learning 101: Training, Goals, and Predictions Explained ๐Ÿš€๐Ÿ“˜ - Topic 010 #ai #ml
deeplizard Beginner 2y ago
Pistol Squat Progression with Mandy + ๐Ÿฆ—
ML Fundamentals
Pistol Squat Progression with Mandy + ๐Ÿฆ—
deeplizard Beginner 2y ago
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Conceptos y Herramientas para la Fรญsica Universitaria
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Conceptos y Herramientas para la Fรญsica Universitaria
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Clinical Decision Support Systems - CDSS 4
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Clinical Decision Support Systems - CDSS 4
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Reinforcement Learning for Trading Strategies
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Reinforcement Learning for Trading Strategies
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Deep Learning Methods for Healthcare
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Deep Learning Methods for Healthcare
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Health Data Science Foundation
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