✳flâneur — a map of the web's best reading
Neural networks and deep learning
neuralnetworksanddeeplearning.com · 18,570 words · saved by 9 readers
If you benefit from the book, please make a small donation. I suggest $5, but you can choose the amount.
Neural networks and deep learning CHAPTER 1 Using neural nets to recognize handwritten digits Neural Networks and Deep Learning What this book is about On the exercises and problems Using neural nets to recognize handwritten digits Perceptrons Sigmoid neurons The architecture of neural networks A simple network to classify handwritten digits Learning with gradient descent Implementing our network to classify digits Toward deep learning How the backpropagation algorithm works Warm up: a fast matrix-based approach to computing the output from a neural network The two assumptions we need about th
Explore this link on the map →saved by
- Klaudia U.
- Jennifer Tsai
- Srushti Ishwarkatti
- abinaya dinesh
- Asma Lamgh
- Stella Jia
- Jianmin Chen
- Saloni Shenoy
- Matthew Siu
related reading
- Neural networks and deep learningneuralnetworksanddeeplearning.com
- Zoom In: An Introduction to Circuitsdistill.pub
- The Little Book of Deep Learningfleuret.org
- Neural networks and deep learningneuralnetworksanddeeplearning.com
- Neural networks and deep learningneuralnetworksanddeeplearning.com
- Gradient descent, how neural networks learn | 3Blue1Brown3blue1brown.com
- Neural networks and deep learningneuralnetworksanddeeplearning.com
- Neural Networks, Manifolds, and Topology -- colah's blogcolah.github.io
- Neural Networks, Types, and Functional Programming -- colah's blogcolah.github.io
- CS231n Deep Learning for Computer Visioncs231n.github.io
- What is backpropagation really doing? | 3Blue1Brown3blue1brown.com
- A Recipe for Training Neural Networkskarpathy.github.io