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
How to Transition into Data Science: from Computer Science to Data Science
ML Fundamentals
How to Transition into Data Science: from Computer Science to Data Science
365 Data Science Beginner 5y ago
Inside TensorFlow: TF Debugging
ML Fundamentals
Inside TensorFlow: TF Debugging
TensorFlow Intermediate 5y ago
MLOps Meetup #6: Mid-Scale Production Feature Engineering with Dr. Venkata Pingali
ML Fundamentals
MLOps Meetup #6: Mid-Scale Production Feature Engineering with Dr. Venkata Pingali
MLOps.community Beginner 5y ago
Intro to Deep Learning -- L15 Autoencoders [Stat453, SS20]
ML Fundamentals
Intro to Deep Learning -- L15 Autoencoders [Stat453, SS20]
Sebastian Raschka Beginner 5y ago
Decoding Logistic Regression - A Simple and Comprehensive Explanation
ML Fundamentals
Decoding Logistic Regression - A Simple and Comprehensive Explanation
What's AI by Louis-François Bouchard Beginner 5y ago
TCP Meltdown - Computerphile
ML Fundamentals
TCP Meltdown - Computerphile
Computerphile Intermediate 5y ago
Theory: Applications of Data Science
ML Fundamentals
Theory: Applications of Data Science
DataCamp Intermediate 5y ago
How deep learning can detect cancerous tissue (AI For Medicine)
ML Fundamentals
How deep learning can detect cancerous tissue (AI For Medicine)
DeepLearningAI Beginner 5y ago
Automate LifeCycle Of Data Science Projects By Using This Open Source Library
ML Fundamentals
Automate LifeCycle Of Data Science Projects By Using This Open Source Library
Krish Naik Beginner 5y ago
Intro to Deep Learning -- L14 Intro to Recurrent Neural Networks [Stat453, SS20]
ML Fundamentals
Intro to Deep Learning -- L14 Intro to Recurrent Neural Networks [Stat453, SS20]
Sebastian Raschka Beginner 5y ago
R Tutorial: Nonlinear Modeling in R with GAMs | Intro
ML Fundamentals
R Tutorial: Nonlinear Modeling in R with GAMs | Intro
DataCamp Beginner 5y ago
Pytorch ResNet implementation from Scratch
ML Fundamentals
Pytorch ResNet implementation from Scratch
Aladdin Persson Beginner 5y ago
PyTorch Tutorial 17 - Saving and Loading Models
ML Fundamentals
PyTorch Tutorial 17 - Saving and Loading Models
Patrick Loeber Beginner 5y ago
Teachable  Machine By Google- Train Your Model With Ease
ML Fundamentals
Teachable Machine By Google- Train Your Model With Ease
Krish Naik Beginner 5y ago
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
ML Fundamentals
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Yannic Kilcher Advanced 5y ago
Dictionaries : Python Basics
ML Fundamentals
Dictionaries : Python Basics
ritvikmath Beginner 5y ago
Demystifying Data Mining - A Clear and Concise Explanation
ML Fundamentals
Demystifying Data Mining - A Clear and Concise Explanation
What's AI by Louis-François Bouchard Beginner 5y ago
This Neural Network Learned To Look Around In Real Scenes! (NERF)
ML Fundamentals
This Neural Network Learned To Look Around In Real Scenes! (NERF)
Two Minute Papers Beginner 6y ago
Neural Networks from Scratch - P.1 Intro and Neuron Code
ML Fundamentals
Neural Networks from Scratch - P.1 Intro and Neuron Code
sentdex Beginner 6y ago
Pytorch Quick Tip: Using a Learning Rate Scheduler
ML Fundamentals
Pytorch Quick Tip: Using a Learning Rate Scheduler
Aladdin Persson Beginner 6y ago
Computer Vision is Not Perfect
ML Fundamentals
Computer Vision is Not Perfect
Data Skeptic Intermediate 6y ago
10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show
ML Fundamentals
10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show
Abhishek Thakur Intermediate 6y ago
Optimization - Lecture 3 - CS50's Introduction to Artificial Intelligence with Python 2020
ML Fundamentals
Optimization - Lecture 3 - CS50's Introduction to Artificial Intelligence with Python 2020
CS50 Beginner 6y ago
Uncertainty - Lecture 2 - CS50's Introduction to Artificial Intelligence with Python 2020
ML Fundamentals
Uncertainty - Lecture 2 - CS50's Introduction to Artificial Intelligence with Python 2020
CS50 Beginner 6y ago
3 key parts to Machine Learning monitoring
ML Fundamentals
3 key parts to Machine Learning monitoring
MLOps.community Intermediate 6y ago
Python Tutorial: Introducing convolutional neural networks
ML Fundamentals
Python Tutorial: Introducing convolutional neural networks
DataCamp Beginner 5y ago
Python Tutorial: Image classification with Keras
ML Fundamentals
Python Tutorial: Image classification with Keras
DataCamp Beginner 5y ago
Python Tutorial: Classifying images
ML Fundamentals
Python Tutorial: Classifying images
DataCamp Beginner 5y ago
Python Tutorial : Data transforms, features, and targets
ML Fundamentals
Python Tutorial : Data transforms, features, and targets
DataCamp Beginner 5y ago
Python Tutorial : Linear modeling with financial data
ML Fundamentals
Python Tutorial : Linear modeling with financial data
DataCamp Beginner 5y ago
Python Tutorial : Machine Learning for Finance in Python
ML Fundamentals
Python Tutorial : Machine Learning for Finance in Python
DataCamp Beginner 5y ago
How to Build A Data Science Portfolio That Can Get You Jobs?
ML Fundamentals
How to Build A Data Science Portfolio That Can Get You Jobs?
Krish Naik Intermediate 5y ago
R Tutorial : Network analysis in R: A tidy approach
ML Fundamentals
R Tutorial : Network analysis in R: A tidy approach
DataCamp Beginner 5y ago
PyTorch Tutorial : Backpropagation by auto-differentiation
ML Fundamentals
PyTorch Tutorial : Backpropagation by auto-differentiation
DataCamp Beginner 5y ago
PyTorch Tutorial : Introduction to PyTorch
ML Fundamentals
PyTorch Tutorial : Introduction to PyTorch
DataCamp Beginner 5y ago
PyTorch Tutorial : Introduction to Neural Networks
ML Fundamentals
PyTorch Tutorial : Introduction to Neural Networks
DataCamp Beginner 5y ago
PyTorch Tutorial : Forward propagation
ML Fundamentals
PyTorch Tutorial : Forward propagation
DataCamp Beginner 5y ago
Python Tutorial : Writing Efficient Python Code
ML Fundamentals
Python Tutorial : Writing Efficient Python Code
DataCamp Beginner 5y ago
Python Tutorial : Introducing XGBoost
ML Fundamentals
Python Tutorial : Introducing XGBoost
DataCamp Beginner 6y ago
Live Q&A Data Science
ML Fundamentals
Live Q&A Data Science
Krish Naik Intermediate 6y ago
Python Tutorial: Class distribution
ML Fundamentals
Python Tutorial: Class distribution
DataCamp Beginner 6y ago
How Should You Explain Your Data Science Projects To Recruiters?- Must Watch For Everyone
ML Fundamentals
How Should You Explain Your Data Science Projects To Recruiters?- Must Watch For Everyone
Krish Naik Intermediate 6y ago
Knowledge - Lecture 1 - CS50's Introduction to Artificial Intelligence with Python 2020
ML Fundamentals
Knowledge - Lecture 1 - CS50's Introduction to Artificial Intelligence with Python 2020
CS50 Beginner 6y ago
Learning - Lecture 4 - CS50's Introduction to Artificial Intelligence with Python 2020
ML Fundamentals
Learning - Lecture 4 - CS50's Introduction to Artificial Intelligence with Python 2020
CS50 Beginner 6y ago
Neural Networks - Lecture 5 - CS50's Introduction to Artificial Intelligence with Python 2020
ML Fundamentals
Neural Networks - Lecture 5 - CS50's Introduction to Artificial Intelligence with Python 2020
CS50 Beginner 6y ago
Pytorch Quick Tip: Weight Initialization
ML Fundamentals
Pytorch Quick Tip: Weight Initialization
Aladdin Persson Beginner 6y ago
Auto retrain ML models is not the question
ML Fundamentals
Auto retrain ML models is not the question
MLOps.community Intermediate 6y ago
Developing a Machine Learning Feature Store
ML Fundamentals
Developing a Machine Learning Feature Store
MLOps.community Intermediate 6y ago
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Modeling Time Series and Sequential Data
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Math for AI beginner part 1 Linear Algebra
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Probabilistic Graphical Models 3: Learning
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