#Autograd
Autograd can automatically differentiate native #Python and #Numpy code.
#Google #JAX
JAX is Autograd and XLA, brought together for high-performance machine learning research.
🔭 @DeepGravity
Autograd can automatically differentiate native #Python and #Numpy code.
#Google #JAX
JAX is Autograd and XLA, brought together for high-performance machine learning research.
🔭 @DeepGravity
GitHub
GitHub - HIPS/autograd: Efficiently computes derivatives of NumPy code.
Efficiently computes derivatives of NumPy code. Contribute to HIPS/autograd development by creating an account on GitHub.
Building #ConvolutionalNeuralNetwork using #NumPy from Scratch
In this article, #CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), #ReLU, and max pooling.
🔭 @DeepGravity
In this article, #CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), #ReLU, and max pooling.
🔭 @DeepGravity
KDnuggets
Building Convolutional Neural Network using NumPy from Scratch
In this article, CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), ReLU, and max pooling.
Dive into Deep Learning
An interactive #DeepLearning #book with code, math, and discussions, based on the #NumPy interface.
Book
🔭 @DeepGravity
An interactive #DeepLearning #book with code, math, and discussions, based on the #NumPy interface.
Book
🔭 @DeepGravity