Top 23 Machine learning Open-Source Projects
An Open Source Machine Learning Framework for EveryoneProject mention: Can someone please help me run this code? | reddit.com/r/learnpython | 2021-03-01
tensorflow 1.3 is not available on pypi anymore. You'll need to download it from github: https://github.com/tensorflow/tensorflow/releases/tag/v1.3.0
Deep Learning for humansProject mention: [D] Batch normalization before or after activation function | reddit.com/r/MachineLearning | 2021-02-23
Get performance insights in less than 4 minutes. Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
Tensors and Dynamic neural networks in Python with strong GPU accelerationProject mention: C++ trainable semantic segmentation models | reddit.com/r/pytorch | 2021-02-28
scikit-learn: machine learning in PythonProject mention: [R] Making changes to sklearn SVC | reddit.com/r/MachineLearning | 2021-02-28
Tesseract Open Source OCR Engine (main repository)Project mention: Introduction to Tesseract & Pytesseract | dev.to | 2021-02-27
➤ Github Tesseract: https://github.com/tesseract-ocr/tesseract ➤ Github PyTesseract: https://github.com/tesseract-ocr/tesseract
The world's simplest facial recognition api for Python and the command lineProject mention: OpenCV or Tensorflow or both ? | reddit.com/r/robotics | 2021-02-21
It’s call face recognition. Face recognition contains two step face detection and face comparison. If you don’t have any background on this I suggest you try the face_recognition python module https://github.com/ageitgey/face_recognition
Deepfakes Software For AllProject mention: Is there a free easy-to-use program to make deepfakes? | reddit.com/r/deepfakememes | 2021-02-17
Caffe: a fast open framework for deep learning.
A complete daily plan for studying to become a machine learning engineer.Project mention: Tips Untuk Pemula Dalam Programming Dan Data | reddit.com/r/indonesia | 2020-09-26
A toolkit for developing and comparing reinforcement learning algorithms.Project mention: "Less intimidating" applications of reinforcement learning | reddit.com/r/datascience | 2021-03-01
The first and the most obvious approach would be to solve the Optical Character Recognition (OCR) task by recognizing the whole text of the image by using, let's say, Tesseract.js library. It returns the bounding boxes of the paragraphs, text lines, and text blocks along with the recognized text.
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
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
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: Resources for learning Python from scratch specifically for data ingestion | reddit.com/r/learnpython | 2021-02-13
data science ipython notebooks
List of Computer Science courses with video lectures.Project mention: I built a collaborative list of resources for developers | reddit.com/r/learnprogramming | 2021-02-04
Cs Video Courses: Developer-Y/cs-video-courses: List of Computer Science courses with video lectures. (github.com)
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimationProject mention: Markerless Motion Capture - Turning Videos into 3D Animations | reddit.com/r/gamedev | 2021-02-13
I just found this open source pose estimation software: https://github.com/CMU-Perceptual-Computing-Lab/openpose
💫 Industrial-strength Natural Language Processing (NLP) in PythonProject mention: PyCon India 2019 | dev.to | 2021-02-25
The opening keynote of the day was Let Them Write Code by Ines Montani, founder of Explosion, core contributor of spaCy, prodigy.
> But you still lose something, e.g. if you use half precision on V100 you get virtually double speed, if you do on a 1080 / 2080 you get... nothing because it's not supported.
That's not true. FP16 is supported and can be fast on 2080, although some frameworks fail to see the speed-up. I filed a bug report about this a year ago: https://github.com/apache/incubator-mxnet/issues/17665
What consumer GPUs lack is ECC and fast FP64.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.Project mention: What are some classification tasks where BERT-based models don't work well? In a similar vein, what are some generative tasks where fine-tuning GPT-2/LM does not work well? | reddit.com/r/LanguageTechnology | 2021-02-21
One place to start is nlp progress if leader boards are your thing, if the model on top of the leader board is not a transformer based model and one further down is, you have your answer.
A curated list of awesome Deep Learning tutorials, projects and communities.
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: Python and Speech recognition | reddit.com/r/learnpython | 2021-02-22
Check Mozilla's common voice. It's a great project, it's easy to participate and easy to use the data. (BTW they've also released DeepSpeech for speech recognition.)
Google ResearchProject mention: [D] Paper Explained - GLOM: How to represent part-whole hierarchies in a neural network (by Geoff Hinton, Full Video Analysis) | reddit.com/r/MachineLearning | 2021-02-27
Iterative consensus (at least under currently proposed frameworks) generally doesn't converge in ways that we want. Hinton makes the assumption that these representations will just naturally converge to detect objects but it's important to remember that NNs have no encoded prior for "objectness". For example, architectures like Slot Attention ( https://github.com/google-research/google-research/tree/master/slot_attention ) already explore this concept of iterative convergence and show good results for object detection in the toy examples used in the paper but if you try to apply that architecture to more complex real-world images you quickly find that it mostly focuses on things like edges and other non-object image features. So the core assumption that this sort of iterative convergence will naturally extract objects is mostly just wishful thinking. Perhaps in the future someone will figure out a way to encode an objectness prior into an architecture and/or loss function but this isn't achieved by any current research for any non-trivial dataset.
Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanicsProject mention: Dungeon Alchemist is AI-powered mapmaking software that auto-populates your rooms with furniture | reddit.com/r/DungeonsAndDragons | 2021-02-19
We use a custom algorithm similar to https://github.com/mxgmn/WaveFunctionCollapse. It learns from examples to figure out how for example a “burial chamber” should look and how objects should be logically placed.
What are some of the best open-source Machine learning projects? This list will help you: