DeepLearning VS analisis-numerico-computo-cientifico

Compare DeepLearning vs analisis-numerico-computo-cientifico and see what are their differences.

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DeepLearning analisis-numerico-computo-cientifico
1 1
3 44
- -
0.0 0.0
almost 2 years ago over 1 year ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
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.

DeepLearning

Posts with mentions or reviews of DeepLearning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-06.

analisis-numerico-computo-cientifico

Posts with mentions or reviews of analisis-numerico-computo-cientifico. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing DeepLearning and analisis-numerico-computo-cientifico you can also consider the following projects:

AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!

osmnx-examples - Gallery of OSMnx tutorials, usage examples, and feature demonstations.

cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

docker-curriculum - :dolphin: A comprehensive tutorial on getting started with Docker!

conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

Deep-Learning-Experiments - Videos, notes and experiments to understand deep learning

Kernels - This is a set of simple programs that can be used to explore the features of a parallel platform.

weightless_NN_decompression - Proof of concept for neural network decompression without storing any weights

laser - The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers

chainerrl - ChainerRL is a deep reinforcement learning library built on top of Chainer.

cocp - Source code for the examples accompanying the paper "Learning convex optimization control policies."