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12 search results found

Deepnet ⭐ 267

Implementations of CNNs, RNNs and deep learning techniques in pure Numpy

Crowded Valley Results ⭐ 129

This repository contains the results for the paper: "Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers"

Cs F425_deep Learning ⭐ 89

CS F425 Deep Learning course at BITS Pilani (Goa Campus)

Deep Learning Optimization Algorithms ⭐ 37

Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.

Adasoptimizer ⭐ 33

ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance

Learning Lab C Library ⭐ 30

This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constantly updated

Lookahead_tensorflow ⭐ 21

Lookahead optimizer ("Lookahead Optimizer: k steps forward, 1 step back") for tensorflow

Gradient Descent Algorithms ⭐ 19

A collection of various gradient descent algorithms implemented in Python from scratch

Haskell Vae ⭐ 17

Learning about Haskell with Variational Autoencoders

Deeplearning_from_scratch ⭐ 16

A Deep Learning framework for CNNs and LSTMs from scratch, using NumPy.

Timeserieslearning ⭐ 14

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

Count Sketch Optimizers ⭐ 10

A compressed adaptive optimizer for training large-scale deep learning models using PyTorch

Coursera Ng Improving Deep Neural Networks Hyperparameter Tuning Regularization And Optimization ⭐ 9

Short description for quick search

Digit Recognizer ⭐ 8

A project I made to practice my newfound Neural Network knowledge - I used Python and Numpy to train a network to recognize MNIST images. Adam and mini-batch gradient descent implemented

ND-Adam is a tailored version of Adam for training DNNs.

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