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Top 23 Python Tensorflow Projects
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Ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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data-science-ipython-notebooks
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.
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d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
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nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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wandb
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
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einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
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deeplake
Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
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Sure, knowing the basics of LLM math is necessary. But it's also _enough_ to know this math to fully grasp the code. There are only 4 concepts - attention, feed-forward net, RMS-normalization and rotary embeddings - organized into a clear structure.
Now compare it to the Hugginface implementation [1]. In addition to the aforementioned concepts, you need to understand the hierarchy of `PreTrainedModel`s, 3 types of attention, 3 types of rotary embeddings, HF's definition of attention mask (which is not the same as mask you read about in transformer tutorials), several types of cache class, dozens of flags to control things like output format or serialization, etc.
It's not that Meta's implementation is good and HF's implementation is bad - they pursue different goals in their own optimal way. But if you just want to learn how the model works, Meta's code base is great.
[1]: https://github.com/huggingface/transformers/blob/main/src/tr...
Keras
In 2019, a new language representation called BERT (Bedirectional Encoder Representation from Transformers) was introduced. The main idea behind this paradigm is to first pre-train a language model using a massive amount of unlabeled data then fine-tune all the parameters using labeled data from the downstream tasks. This allows the model to generalize well to different NLP tasks. Moreover, it has been shown that this language representation model can be used to solve downstream tasks without being explicitly trained on, e.g classify a text without training phase.
Project mention: Ray: Unified framework for scaling AI and Python applications | news.ycombinator.com | 2024-05-03
virtual dj and others stem separator is shrinked model of this https://github.com/deezer/spleeter you will get better results downloading original + their large model.
Project mention: Intuituvely Understanding Harris Corner Detector | news.ycombinator.com | 2023-09-11The most widely used algorithms for classical feature detection today are "whatever opencv implements"
In terms of tech that's advancing at the moment? https://co-tracker.github.io/ if you want to track individual points, https://github.com/matterport/Mask_RCNN and its descendents if you want to detect, say, the cover of a book.
Project mention: 🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇 | dev.to | 2023-10-19
Project mention: License Plate Recognition with Home Assistant, Codeproject.ai, and Frigate NVR | news.ycombinator.com | 2024-04-26
You can always slice the images into smaller ones, run detection on each tile, and combine results. Supervision has a utility for this - https://supervision.roboflow.com/latest/detection/tools/infe..., but it only works with detections. You can get a much more accurate result this way. Here is some side-by-side comparison: https://github.com/roboflow/supervision/releases/tag/0.14.0.
See also https://github.com/unifyai/ivy which I have not tried but seems along the lines of what you are describing, working with all the major frameworks
Project mention: A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev | dev.to | 2024-02-05Weights & Biases — The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management. Free tier for personal projects only, with 100 GB of storage included.
Not sure if the wrapper you’re talking about is your own custom code, but I really like using einops lately. It’s got similar axis naming capabilities and it dispatches to both numpy and pytorch
http://einops.rocks/
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python Tensorflow related posts
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Apple to Power AI Features with M2 Ultra Servers
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XLSTM: Extended Long Short-Term Memory
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Zero Shot Text Classification Under the hood
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License Plate Recognition with Home Assistant, Codeproject.ai, and Frigate NVR
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My Favorite DevTools to Build AI/ML Applications!
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Release: Keras 3.3.0
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Multimillion-dollar L.A. heist was seamless, sophisticated, stealthy
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A note from our sponsor - InfluxDB
www.influxdata.com | 17 May 2024
Index
What are some of the best open-source Tensorflow projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | transformers | 126,170 |
| 2 | Keras | 61,044 |
| 3 | Real-Time-Voice-Cloning | 50,951 |
| 4 | bert | 37,119 |
| 5 | Ray | 31,414 |
| 6 | data-science-ipython-notebooks | 26,532 |
| 7 | spleeter | 25,003 |
| 8 | Mask_RCNN | 24,201 |
| 9 | d2l-en | 21,858 |
| 10 | datasets | 18,480 |
| 11 | best-of-ml-python | 15,633 |
| 12 | frigate | 15,006 |
| 13 | supervision | 14,673 |
| 14 | ivy | 14,025 |
| 15 | horovod | 13,987 |
| 16 | nni | 13,777 |
| 17 | facenet | 13,525 |
| 18 | TFLearn | 9,608 |
| 19 | autokeras | 9,076 |
| 20 | wandb | 8,294 |
| 21 | einops | 7,971 |
| 22 | python-small-examples | 7,841 |
| 23 | deeplake | 7,734 |
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