datasets
examples
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datasets | examples | |
---|---|---|
5 | 143 | |
4,175 | 7,754 | |
1.5% | 1.4% | |
9.4 | 5.3 | |
4 days ago | 27 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
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.
datasets
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TensorFlow Datasets (TFDS): a collection of ready-to-use datasets
I tried Librispeech, a very common dataset for speech recognition, in both HF and TFDS.
TFDS performed extremely bad.
First it failed because the official hosting server only allows 5 simultaneous connections, and TFDS totally ignored that and makes up to 50 simultaneous downloads and that breaks. I wonder if anyone actually tested this?
Then you need to have some computer with 30GB to do the preparation, which might fail on your computer. This is where I stopped. https://github.com/tensorflow/datasets/issues/3887. It might be fixed now but it took them 8 months to respond to my issue.
On HF, it just worked. There was a smaller issue in how the dataset was split up but that is fixed now, and their response was very fast and great.
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We built a pi controlled hydroponics box that grows your plants 1.5x faster using ML
but it looks like none of your plants are supported by the plantvillage model, or do I understand something wrong? https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/image_classification/plant_village.py#L57
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Voice Recognition with Tensorflow
To do our example, we're going to use some audio files released by Google.
examples
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
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MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
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🔥14 Excellent Open-source Projects for Developers😎
10. TensorFlow - Make Machine Learning Work for You 🤖
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GPU Survival Toolkit for the AI age: The bare minimum every developer must know
AI models, particularly those built on deep learning frameworks like TensorFlow, exhibit a high degree of parallelism. Neural network training involves numerous matrix operations, and GPUs, with their expansive core count, excel in parallelizing these operations. TensorFlow, along with other popular deep learning frameworks, optimizes to leverage GPU power for accelerating model training and inference.
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
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Tensorflow help
I am on a new ftc team trying to get vision to work. I used the ftc machine learning tool chain but I have yet to get a good result with at best a 10% accuracy rate. I have changed everything possible in the tool chain with little luck. To fix this, I have tried making my own .tflite model using the google colab from https://www.tensorflow.org/. When ever I try to run the same code with my own .tflite model, it gives me the error "User code threw an uncaught exception: IllegalStateException - Error getting native address of native library: task_vision_jni". It gives me the same error with official tensor flow tflite test models, and when I put them on a raspberry pi, both worked just fine. Does anyone have a fix to this error or even just tips for the machine learning toolchain?
What are some alternatives?
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
cppflow - Run TensorFlow models in C++ without installation and without Bazel
flax - Flax is a neural network library for JAX that is designed for flexibility.
mlpack - mlpack: a fast, header-only C++ machine learning library
jax-models - Unofficial JAX implementations of deep learning research papers
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
FedScale - FedScale is a scalable and extensible open-source federated learning (FL) platform.
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
trax - Trax — Deep Learning with Clear Code and Speed
Selenium WebDriver - A browser automation framework and ecosystem.
jaxopt - Hardware accelerated, batchable and differentiable optimizers in JAX.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing