DeepNeuralNetworksFromScratch VS dl-4-tsc

Compare DeepNeuralNetworksFromScratch vs dl-4-tsc and see what are their differences.

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DeepNeuralNetworksFromScratch dl-4-tsc
1 5
8 1,447
- -
0.0 1.9
over 1 year ago about 1 year ago
Python Python
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DeepNeuralNetworksFromScratch

Posts with mentions or reviews of DeepNeuralNetworksFromScratch. We have used some of these posts to build our list of alternatives and similar projects.

dl-4-tsc

Posts with mentions or reviews of dl-4-tsc. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing DeepNeuralNetworksFromScratch and dl-4-tsc you can also consider the following projects:

IntroDLPython - This repository is updated by a number of introductory projects to deep learning with Python.

neozot-py - get recommendations from arxiv based on your zotero library

dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).

ietf-reviewtool - Download and review IETF documents, such as Internet-Drafts or RFCs.

SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.

hydra - HYDRA: Competing convolutional kernels for fast and accurate time series classification

Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.

Convolution-From-Scratch - Implementation of the generalized 2D convolution with dilation from scratch in Python and NumPy

pyradox - State of the Art Neural Networks for Deep Learning