up-for-grabs.net VS examples

Up-for-Grabs projects: Find issues specifically marked for beginner contributions.

Up For Grabs maintains a “list of open source projects which have curated tasks specifically for new contributors.” (Source: Up For Grabs)

If you're unsure where to begin, websites like Up For Grabs can be valuable resources. They curate lists of open source projects that actively seek contributions, making it easier for you to find projects that are suitable for your skills and interests. These platforms provide a starting point for your research and help you navigate the vast space of open source projects.

the sidebar links http://up-for-grabs.net/

Up For Grabs - a website that lists beginner-friendly open-source projects

Up For Grabs

Up for Grabs : This is a list of projects which have curated tasks specifically for new contributors. These are a great way to get started with a project or to help share the load of working on open source projects.

Maybe you can find something in this site https://up-for-grabs.net/

up-for-grabs, goodfirstissue.dev, goodfirstissues.com, and opensourcehub.io are some places folks can look for projects to contribute to. Of course, maintainers could also get their projects listed there to attract contributors.

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.

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.

TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.

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.

10. TensorFlow - Make Machine Learning Work for You 🤖

#2 TensorFlow

Machine learning is the process of using algorithms and statistical models to enable computers to learn from data. There are many tools and libraries available for machine learning, but the most popular by far is TensorFlow. TensorFlow is an open-source platform for machine learning developed by Google. It has over 176k stars on Github and is used by companies such as Airbnb and Intel.

Tensorflow is Google's "end-to-end machine learning platform". It's a framework to manage the whole lifecycle of a Machine Learning (and AI) project, from data preparation to production deployment. Remember the math stuff we talked about in the last section? Tensorflow manages that in addition to a lot of other stuff. Its core API is written for Python and you have to know your math just a little bit in order to play with it. It's more for deep learning models (neural networks) and has a lot of already implemented "layers" for you to use in your network. You can prepare data (images included with the option of image augmentation for small data sets ... yay! 😃), experiment with different model architectures, tune the model's hyperparameters (a fancy name for model configs), train, validate and test your models and monitor your models in production. It's a great framework, but it is not an easy one to learn, especially if you don't like math that much!

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