✕ Clear filters
8,493 lessons

📐 ML Fundamentals

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

All ▶ YouTube 198,949📚 Coursera 18,124🎤 TED 1
Introduction To Statistics And Its Types For Starters
📐 ML Fundamentals
Introduction To Statistics And Its Types For Starters
Krish Naik Beginner 4y ago
MLOps Memes // Ariel Biller // MLOps Coffee Sessions #37
📐 ML Fundamentals
MLOps Memes // Ariel Biller // MLOps Coffee Sessions #37
MLOps.community Beginner 4y ago
GNN Project #1 - Introduction to HIV dataset
📐 ML Fundamentals
GNN Project #1 - Introduction to HIV dataset
DeepFindr Beginner 4y ago
TensorFlow for Deep Learning course Udemy launch Q&A (live)
📐 ML Fundamentals
TensorFlow for Deep Learning course Udemy launch Q&A (live)
Daniel Bourke Beginner 4y ago
AutoML Frameworks Accuracy Comparison with Kaggle Data - Automated Machine Learning
📐 ML Fundamentals
AutoML Frameworks Accuracy Comparison with Kaggle Data - Automated Machine Learning
1littlecoder Beginner 4y ago
Polly Fordyce — Microfluidic Platforms and Machine Learning
📐 ML Fundamentals
Polly Fordyce — Microfluidic Platforms and Machine Learning
Weights & Biases Beginner 4y ago
What is machine learning lifecycle? | What is Model Development Life Cycle (MDLC)? MDLC vs SDLC
📐 ML Fundamentals
What is machine learning lifecycle? | What is Model Development Life Cycle (MDLC)? MDLC vs SDLC
codebasics Beginner 4y ago
Explainable AI Cheat Sheet - Five Key Categories
📐 ML Fundamentals
Explainable AI Cheat Sheet - Five Key Categories
Jay Alammar Beginner 4y ago
Community Detection : Data Science Concepts
📐 ML Fundamentals
Community Detection : Data Science Concepts
ritvikmath Beginner 4y ago
All Type Of Cross Validation With Python All In 1 Video
📐 ML Fundamentals
All Type Of Cross Validation With Python All In 1 Video
Krish Naik Beginner 4y ago
OSLP - Postcards from a Pandemic - Tracey Camilleri
📐 ML Fundamentals
OSLP - Postcards from a Pandemic - Tracey Camilleri
Saïd Business School, University of Oxford Beginner 4y ago
W&B Deep Learning Salon - Pulkit Agrawal
📐 ML Fundamentals
W&B Deep Learning Salon - Pulkit Agrawal
Weights & Biases Beginner 4y ago
Community Updates by  Suraj Subramanian | PyTorch Ecosystem Day 2021
📐 ML Fundamentals
Community Updates by Suraj Subramanian | PyTorch Ecosystem Day 2021
PyTorch Beginner 4y ago
Applications of AI and PyTorch in Asia Pacific by Ritchie Ng | PyTorch Ecosystem Day 2021
📐 ML Fundamentals
Applications of AI and PyTorch in Asia Pacific by Ritchie Ng | PyTorch Ecosystem Day 2021
PyTorch Beginner 4y ago
L18.6: A DCGAN for Generating Face Images in PyTorch -- Code Example
📐 ML Fundamentals
L18.6: A DCGAN for Generating Face Images in PyTorch -- Code Example
Sebastian Raschka Beginner 4y ago
L18.5: Tips and Tricks to Make GANs Work
📐 ML Fundamentals
L18.5: Tips and Tricks to Make GANs Work
Sebastian Raschka Beginner 4y ago
Normal Distribution and Z Score | Math, Statistics for data science, machine learning
📐 ML Fundamentals
Normal Distribution and Z Score | Math, Statistics for data science, machine learning
codebasics Beginner 4y ago
Pandemic Machine Learning Pitfalls
📐 ML Fundamentals
Pandemic Machine Learning Pitfalls
Data Skeptic Beginner 4y ago
Decision and Classification Trees, Clearly Explained!!!
📐 ML Fundamentals
Decision and Classification Trees, Clearly Explained!!!
StatQuest with Josh Starmer Beginner 4y ago
Text Generation without Deep Learning - Markov Chain in Python
📐 ML Fundamentals
Text Generation without Deep Learning - Markov Chain in Python
1littlecoder Beginner 4y ago
Luigi in Production Part 2 // Luigi Patruno // MLOps Coffee Sessions #36
📐 ML Fundamentals
Luigi in Production Part 2 // Luigi Patruno // MLOps Coffee Sessions #36
MLOps.community Beginner 4y ago
Natural Language Processing (NLP) and Text Classification With Python
📐 ML Fundamentals
Natural Language Processing (NLP) and Text Classification With Python
Real Python Beginner 4y ago
Banking for Climate Change Mitigation: Opportunities and Challenges
📐 ML Fundamentals
Banking for Climate Change Mitigation: Opportunities and Challenges
Saïd Business School, University of Oxford Beginner 4y ago
Backpropagation : Data Science Concepts
📐 ML Fundamentals
Backpropagation : Data Science Concepts
ritvikmath Beginner 4y ago
Node-Red: Visual coding for ML on Raspberry Pi and beyond - Made with TensorFlow.js
📐 ML Fundamentals
Node-Red: Visual coding for ML on Raspberry Pi and beyond - Made with TensorFlow.js
TensorFlow Beginner 4y ago
1. Live coding Jarvis Transcriptions for Speech to Text Dataset p.1
📐 ML Fundamentals
1. Live coding Jarvis Transcriptions for Speech to Text Dataset p.1
sentdex Beginner 4y ago
Drawdata-Python Library To Draw Dataset In Jupyter Notebook
📐 ML Fundamentals
Drawdata-Python Library To Draw Dataset In Jupyter Notebook
Krish Naik Beginner 4y ago
Detect Duplicate Images in Python with CNN using imagededup | Kaggle Notebook
📐 ML Fundamentals
Detect Duplicate Images in Python with CNN using imagededup | Kaggle Notebook
1littlecoder Beginner 4y ago
Deep Learning Interview Series #2- Asked In interview
📐 ML Fundamentals
Deep Learning Interview Series #2- Asked In interview
Krish Naik Beginner 4y ago
Train and Debug YOLOv5 Models with Weights & Biases Integration | YOLOv5 Series Part 0
📐 ML Fundamentals
Train and Debug YOLOv5 Models with Weights & Biases Integration | YOLOv5 Series Part 0
Weights & Biases Beginner 4y ago
L18.4: A GAN for Generating Handwritten Digits in PyTorch -- Code Example
📐 ML Fundamentals
L18.4: A GAN for Generating Handwritten Digits in PyTorch -- Code Example
Sebastian Raschka Beginner 4y ago
L18.3: Modifying the GAN Loss Function for Practical Use
📐 ML Fundamentals
L18.3: Modifying the GAN Loss Function for Practical Use
Sebastian Raschka Beginner 4y ago
L18.2: The GAN Objective
📐 ML Fundamentals
L18.2: The GAN Objective
Sebastian Raschka Beginner 4y ago
L18.1: The Main Idea Behind GANs
📐 ML Fundamentals
L18.1: The Main Idea Behind GANs
Sebastian Raschka Beginner 4y ago
L18.0: Introduction to Generative Adversarial Networks -- Lecture Overview
📐 ML Fundamentals
L18.0: Introduction to Generative Adversarial Networks -- Lecture Overview
Sebastian Raschka Beginner 4y ago
Adrien Gaidon — Advancing ML Research in Autonomous Vehicles
📐 ML Fundamentals
Adrien Gaidon — Advancing ML Research in Autonomous Vehicles
Weights & Biases Beginner 4y ago
MLOps Community 1 Year Anniversary! // Meetup #59 clip
📐 ML Fundamentals
MLOps Community 1 Year Anniversary! // Meetup #59 clip
MLOps.community Beginner 4y ago
L17.7 VAE Latent Space Arithmetic in PyTorch -- Making People Smile (Code Example)
📐 ML Fundamentals
L17.7 VAE Latent Space Arithmetic in PyTorch -- Making People Smile (Code Example)
Sebastian Raschka Beginner 4y ago
L17.6 A Variational Autoencoder for Face Images in PyTorch -- Code Example
📐 ML Fundamentals
L17.6 A Variational Autoencoder for Face Images in PyTorch -- Code Example
Sebastian Raschka Beginner 4y ago
L17.5 A Variational Autoencoder for Handwritten Digits in PyTorch -- Code Example
📐 ML Fundamentals
L17.5 A Variational Autoencoder for Handwritten Digits in PyTorch -- Code Example
Sebastian Raschka Beginner 4y ago
L17.4 Variational Autoencoder Loss Function
📐 ML Fundamentals
L17.4 Variational Autoencoder Loss Function
Sebastian Raschka Beginner 4y ago
L17.3 The Log-Var Trick
📐 ML Fundamentals
L17.3 The Log-Var Trick
Sebastian Raschka Beginner 4y ago
L17.2 Sampling from a Variational Autoencoder
📐 ML Fundamentals
L17.2 Sampling from a Variational Autoencoder
Sebastian Raschka Beginner 4y ago
L17.1 Variational Autoencoder Overview
📐 ML Fundamentals
L17.1 Variational Autoencoder Overview
Sebastian Raschka Beginner 4y ago
L17.0 Intro to Variational Autoencoders -- Lecture Overview
📐 ML Fundamentals
L17.0 Intro to Variational Autoencoders -- Lecture Overview
Sebastian Raschka Beginner 4y ago
Machine Learning Interview Series#1-Asked in Interview
📐 ML Fundamentals
Machine Learning Interview Series#1-Asked in Interview
Krish Naik Beginner 4y ago
War Stories Productionising ML // Nick Masca // Coffee Session#35
📐 ML Fundamentals
War Stories Productionising ML // Nick Masca // Coffee Session#35
MLOps.community Beginner 4y ago
Intro to Neural Networks : Data Science Concepts
📐 ML Fundamentals
Intro to Neural Networks : Data Science Concepts
ritvikmath Beginner 4y ago
📚 Coursera Courses Opens on Coursera · Free to audit
1 / 3 View all →
Practical Machine Learning
📚 Coursera Course ↗
Self-paced
Practical Machine Learning
Opens on Coursera ↗
Apply Artificial Intelligence Using Python for Beginners
📚 Coursera Course ↗
Self-paced
Apply Artificial Intelligence Using Python for Beginners
Opens on Coursera ↗
Detecting COVID-19 with Chest X-Ray using PyTorch
📚 Coursera Course ↗
Self-paced
Detecting COVID-19 with Chest X-Ray using PyTorch
Opens on Coursera ↗
AWS: Model Training , Optimization & Deployment
📚 Coursera Course ↗
Self-paced
AWS: Model Training , Optimization & Deployment
Opens on Coursera ↗
Introduction to Social Media Analytics
📚 Coursera Course ↗
Self-paced
Introduction to Social Media Analytics
Opens on Coursera ↗
Statistics and Calculus Methods for Data Analysis
📚 Coursera Course ↗
Self-paced
Statistics and Calculus Methods for Data Analysis
Opens on Coursera ↗