Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
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Updated
Oct 2, 2020 - Jupyter Notebook
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Educational deep learning library in plain Numpy.
A tour of different optimization algorithms in PyTorch.
A collection of various gradient descent algorithms implemented in Python from scratch
A compressed adaptive optimizer for training large-scale deep learning models using PyTorch
Simple MATLAB toolbox for deep learning network: Version 1.0.3
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.
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
Performing sentiment analysis on tweets obtained from twitter.
Repository for machine learning problems implemented in python
SC-Adagrad, SC-RMSProp and RMSProp algorithms for training deep networks proposed in
Implementation of Convex Optimization algorithms
Package used for mathematical optimization.
implementation of factorization machine, support classification.
Hands on implementation of gradient descent based optimizers in raw python
Deep Learning Optimizers
Contains my custom implementation of various machine learning models and analysis.
a python script of a function summarize some popular methods about gradient descent
Library which can be used to build feed forward NN, Convolutional Nets, Linear Regression, and Logistic Regression Models.
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