Top 23 Deep Learning Open-Source Projects
An Open Source Machine Learning Framework for EveryoneProject mention: Need help with tensorflow library installed in mac m1 | reddit.com/r/MacOS | 2021-10-17
I think this subreddit is probably the last place you'll find decent support for Tensorflow. I recommend opening up an issue on Github.
Open Source Computer Vision LibraryProject mention: [Question] How do I prevent the ROI output message? | reddit.com/r/opencv | 2021-10-13
Optimize your datasets for ML. Goodbye, boilerplate code - the fastest dataset optimization and management tool for computer vision.
Deep Learning for humansProject mention: Steps_per_epoch=1 | reddit.com/r/tensorflow | 2021-10-18
I think I found my answer here Thank you for your help
Tensors and Dynamic neural networks in Python with strong GPU accelerationProject mention: Source to learn pytorch? | reddit.com/r/pytorch | 2021-10-18
For starters your best bet might be the tuts from https://pytorch.org/ . After that, you might find these helpful..
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)Project mention: Keras vs. TensorFlow | dev.to | 2021-06-06
A linear regression model
Deepfakes Software For AllProject mention: Is it just me, or is faceswap installation trolling me? | reddit.com/r/faceswap | 2021-08-18
It keeps getting stuck at either"fatal: unable to access 'https://github.com/deepfakes/faceswap.git/':" or "Please run this script with Python version 3.7 or 3.8 64bit and try again."
Caffe: a fast open framework for deep learning.Project mention: Una corta intro a las Redes Neuronales Artificiales | dev.to | 2021-09-22
Caffe de BAIR
Run Linux Software Faster and Safer than Linux with Unikernels.
Clone a voice in 5 seconds to generate arbitrary speech in real-timeProject mention: Is there a free (preferably open source) offline invoice creation software for windows 10? | reddit.com/r/software | 2021-09-27
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!Project mention: [D] Resources for Understanding The Original Transformer Paper | reddit.com/r/MachineLearning | 2021-09-08
https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap - This one is a bit dated so it doesn’t contain all of the papers that you need to read to get up to date but I think you should definitely read all of the papers in this list and implement as much as you can.
DeepFaceLab is the leading software for creating deepfakes.Project mention: Yararlı olabilecek Github Python repoları | reddit.com/r/AtaturkKutuphanesi | 2021-10-13
Learn how to responsibly deliver value with ML.Project mention: mlops with mlflow | reddit.com/r/mlops | 2021-10-11
My recommendation for newbies is first to do this course: https://madewithml.com/
A complete daily plan for studying to become a machine learning engineer.Project mention: Plano de estudos em machine learning com conteúdos em português. | dev.to | 2021-08-18
Have you tried this version?
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimationProject mention: Help finding an appropriate model for human pose estimation | reddit.com/r/computervision | 2021-09-29
Openpose: This is supposedly realtime (I assume on a gpu, 24fps?) and they provide training code
PyTorch Tutorial for Deep Learning ResearchersProject mention: How to 'practice' pytorch after finishing its basic tutorial? | reddit.com/r/learnmachinelearning | 2021-05-09
I tried to move straight to practicing implementing papers and trying to understand other people's codes but failed miserably. I feel like there was too much of a gap between the basic tutorial and being able to implement ideas into code....hence the question: Is there any resource/way to practice pytorch in general? I did find this and this, but I just wanted to hear what others have gone through to become better at PyTorch up to the point they can build stuff from their own ideas
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.Project mention: Beginner in Python for Data Science | reddit.com/r/learnpython | 2020-12-27
data science ipython notebooks
The fastai deep learning libraryProject mention: D I Refuse To Use Pytorch Because Its A Facebook | reddit.com/r/MachineLearning | 2020-12-29
Also, not a single docstring to document any code in the library - https://github.com/fastai/fastai/blob/master/fastai/vision/learner.py
💫 Industrial-strength Natural Language Processing (NLP) in PythonProject mention: Parsing Addresses With Machine Learning | dev.to | 2021-10-18
A key feature of our address verification product is speed. Therefore, the library we chose to help build our address parser had to be up for the task. After comparing a few options, we chose spaCy. Given its state-of-the-art speed, named entity recognition feature, and documentation, spaCy is very suitable for this task.
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.Project mention: Offline speech to text software | reddit.com/r/AskTechnology | 2021-10-16
A curated list of awesome Deep Learning tutorials, projects and communities.
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.Project mention: How to deploy a rllib-trained model? | reddit.com/r/reinforcementlearning | 2021-10-16
Deezer source separation library including pretrained models.Project mention: does a sub exist where helpful people are up for removing background sound from audio? | reddit.com/r/findareddit | 2021-10-04
Try spleeter out: https://github.com/deezer/spleeter
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet ) (by AlexeyAB)Project mention: [D] Best way to publish code for a paper | reddit.com/r/MachineLearning | 2021-10-07
So you can do it, it's better, but people won't blame you if you don't do it as long as the code you publish do work. And as long as it's not too obscure.
What are some of the best open-source Deep Learning projects? This list will help you:
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