DeepLearning VS Deep-Learning-Experiments

Compare DeepLearning vs Deep-Learning-Experiments and see what are their differences.

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DeepLearning Deep-Learning-Experiments
1 1
3 1,081
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0.0 8.3
almost 2 years ago about 1 month ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.

Deep-Learning-Experiments

Posts with mentions or reviews of Deep-Learning-Experiments. We have used some of these posts to build our list of alternatives and similar projects.
  • EEE 197 - Deep Learning
    1 project | /r/peyups | 25 Aug 2022
    Hello, took the course last sem. Maraming napa-drop sa amin dahil sa difficulty nung assignments pero doable naman. Open-source mismo yung course, available sya sa GitHub: https://github.com/roatienza/Deep-Learning-Experiments

What are some alternatives?

When comparing DeepLearning and Deep-Learning-Experiments you can also consider the following projects:

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

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).

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

adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

python_autocomplete - Use Transformers and LSTMs to learn Python source code

analisis-numerico-computo-cientifico - Análisis numérico y cómputo científico

nn - 🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

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

pytorch-deepdream - PyTorch implementation of DeepDream algorithm (Mordvintsev et al.). Additionally I've included playground.py to help you better understand basic concepts behind the algo.

monodepth2 - [ICCV 2019] Monocular depth estimation from a single image

TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)