Coursera Neural Networks and Machine Learning Geoffrey Hinton University of Toronto The Bayesian interpretation of weight decay 11 min mp4

Coursera Neural Networks and Machine Learning Geoffrey Hinton University of Toronto
The Bayesian interpretation of weight decay 11 min mp4

Name	Coursera_Neural-Networks-and-Machine-Learning_Geoffrey-Hinton_University-of-Toronto	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	558.5 MB
Total Files	49
Last Seen	2025-03-26 23:30
Hash	BA102098008A21226094AFEC8A2C6A7F25276E5C

/9 - 5 - The Bayesian interpretation of weight decay [11 min].mp4	12.9 MB
/2 - 5 - What perceptrons cant do [15 min].mp4	17.4 MB
/3 - 4 - The backpropagation algorithm [12 min].mp4	14.0 MB
/4 - 1 - Learning to predict the next word [13 min].mp4	15.0 MB
/1 - 5 - Three types of learning [8 min].mp4	9.4 MB
/5 - 1 - Why object recognition is difficult [5 min].mp4	5.6 MB
/9 - 2 - Limiting the size of the weights [6 min].mp4	7.7 MB
/1 - 2 - What are neural networks [8 min].mp4	10.2 MB
/1 - 4 - A simple example of learning [6 min].mp4	6.9 MB
/10 - 1 - Why it helps to combine models [13 min].mp4	15.9 MB
/3 - 1 - Learning the weights of a linear neuron [12 min].mp4	14.2 MB
/3 - 2 - The error surface for a linear neuron [5 min].mp4	6.2 MB
/9 - 3 - Using noise as a regularizer [7 min].mp4	8.9 MB
/1 - 1 - Why do we need machine learning [13 min].mp4	15.8 MB
/2 - 1 - Types of neural network architectures [7 min].mp4	9.2 MB
Showing first 15 files of 49 total files