Видео ютуба по тегу Neural Network Demystified

Neural Networks Demystified [Part 1: Data and Architecture]
Neural Networks Demystified [Part 1: Data and Architecture]
Neural Networks Demystified [Part 2: Forward Propagation]
Neural Networks Demystified [Part 2: Forward Propagation]
NLP Demystified 10: Neural Networks From Scratch
NLP Demystified 10: Neural Networks From Scratch
Neural Networks Demystified [Part 4: Backpropagation]
Neural Networks Demystified [Part 4: Backpropagation]
But what is a neural network? | Deep learning chapter 1
But what is a neural network? | Deep learning chapter 1
Neural Networks Demystified [Part 6: Training]
Neural Networks Demystified [Part 6: Training]
Neural Networks Demystified [Part 7: Overfitting, Testing, and Regularization]
Neural Networks Demystified [Part 7: Overfitting, Testing, and Regularization]
Neural Networks Demystified: Part 7, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 7, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 2, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 2, Welch Labs @ MLconf SF
Neural Networks Demystified: The Key to Understanding AI & Machine Learning!
Neural Networks Demystified: The Key to Understanding AI & Machine Learning!
Demystifying Neural Network: A Beginner's Guide to Machine Learning Fundamentals
Demystifying Neural Network: A Beginner's Guide to Machine Learning Fundamentals
Neural Networks Demystified: Part 5, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 5, Welch Labs @ MLconf SF
Neural Networks Demystified [Part 3: Gradient Descent]
Neural Networks Demystified [Part 3: Gradient Descent]
Neural Networks Demystified: Part 6, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 6, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 1, Welch Labs @ MLconf SF
Neural Networks Demystified: Part 1, Welch Labs @ MLconf SF
[Neural Network 7] Backpropagation Demystified: A Step-by-Step Guide to the Heart of Neural Networks
[Neural Network 7] Backpropagation Demystified: A Step-by-Step Guide to the Heart of Neural Networks