📐 ML Fundamentals

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

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Intro to Deep Learning -- L15 Autoencoders [Stat453, SS20]

ML Fundamentals

Intro to Deep Learning -- L15 Autoencoders [Stat453, SS20]

Sebastian Raschka Beginner 6y 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 6y ago

Theory: Applications of Data Science

ML Fundamentals ⚡ AI Lesson

Theory: Applications of Data Science

DataCamp Intermediate 6y 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 6y 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 6y ago

Intro to Deep Learning -- L14 Intro to Recurrent Neural Networks [Stat453, SS20]

ML Fundamentals ⚡ AI Lesson

Intro to Deep Learning -- L14 Intro to Recurrent Neural Networks [Stat453, SS20]

Sebastian Raschka Beginner 6y ago

R Tutorial: Nonlinear Modeling in R with GAMs | Intro

ML Fundamentals

R Tutorial: Nonlinear Modeling in R with GAMs | Intro

DataCamp Beginner 6y ago

Pytorch ResNet implementation from Scratch

ML Fundamentals

Pytorch ResNet implementation from Scratch

Aladdin Persson Beginner 6y ago

PyTorch Tutorial 17 - Saving and Loading Models

ML Fundamentals ⚡ AI Lesson

PyTorch Tutorial 17 - Saving and Loading Models

Patrick Loeber Beginner 6y ago

Teachable Machine By Google- Train Your Model With Ease

ML Fundamentals

Teachable Machine By Google- Train Your Model With Ease

Krish Naik Beginner 6y ago

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

ML Fundamentals

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Yannic Kilcher Advanced 6y 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 6y 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 ⚡ AI Lesson

Computer Vision is Not Perfect

Data Skeptic Intermediate 6y ago

10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show

ML Fundamentals ⚡ AI Lesson

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

Auto retrain ML models is not the question

ML Fundamentals ⚡ AI Lesson

Auto retrain ML models is not the question

MLOps.community Intermediate 6y ago

Python Tutorial: Introducing convolutional neural networks

ML Fundamentals ⚡ AI Lesson

Python Tutorial: Introducing convolutional neural networks

DataCamp Beginner 6y ago

Python Tutorial: Image classification with Keras

ML Fundamentals

Python Tutorial: Image classification with Keras

DataCamp Beginner 6y ago

Python Tutorial: Classifying images

ML Fundamentals

Python Tutorial: Classifying images

DataCamp Beginner 6y ago

Python Tutorial : Data transforms, features, and targets

ML Fundamentals ⚡ AI Lesson

Python Tutorial : Data transforms, features, and targets

DataCamp Beginner 6y ago

Python Tutorial : Linear modeling with financial data

ML Fundamentals ⚡ AI Lesson

Python Tutorial : Linear modeling with financial data

DataCamp Beginner 6y ago

Python Tutorial : Machine Learning for Finance in Python

ML Fundamentals

Python Tutorial : Machine Learning for Finance in Python

DataCamp Beginner 6y 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 6y ago

R Tutorial : Network analysis in R: A tidy approach

ML Fundamentals

R Tutorial : Network analysis in R: A tidy approach

DataCamp Beginner 6y ago

PyTorch Tutorial : Backpropagation by auto-differentiation

ML Fundamentals

PyTorch Tutorial : Backpropagation by auto-differentiation

DataCamp Beginner 6y ago

PyTorch Tutorial : Introduction to PyTorch

ML Fundamentals

PyTorch Tutorial : Introduction to PyTorch

DataCamp Beginner 6y ago

PyTorch Tutorial : Introduction to Neural Networks

ML Fundamentals

PyTorch Tutorial : Introduction to Neural Networks

DataCamp Beginner 6y ago

PyTorch Tutorial : Forward propagation

ML Fundamentals ⚡ AI Lesson

PyTorch Tutorial : Forward propagation

DataCamp Beginner 6y ago

Python Tutorial : Writing Efficient Python Code

ML Fundamentals

Python Tutorial : Writing Efficient Python Code

DataCamp Beginner 6y 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 ⚡ AI Lesson

Pytorch Quick Tip: Weight Initialization

Aladdin Persson Beginner 6y ago

Developing a Machine Learning Feature Store

ML Fundamentals

Developing a Machine Learning Feature Store

MLOps.community Intermediate 6y ago

Evolution of the ML feature store @SurveyMonkey

ML Fundamentals

Evolution of the ML feature store @SurveyMonkey

MLOps.community Intermediate 6y ago

Doing ML with Personal Information

ML Fundamentals ⚡ AI Lesson

Doing ML with Personal Information

MLOps.community Intermediate 6y ago

How do you handle ML version control at SurveyMonkey

ML Fundamentals

How do you handle ML version control at SurveyMonkey

MLOps.community Intermediate 6y ago

Hybrid Data Science Teams @SurveyMonkey

ML Fundamentals ⚡ AI Lesson

Hybrid Data Science Teams @SurveyMonkey

MLOps.community Intermediate 6y ago

Message buses, Async and sync architecture

ML Fundamentals

Message buses, Async and sync architecture

MLOps.community Intermediate 6y ago