MindsDB VS tensorflow

If you would like to find out more about MindsDB, you can visit their website.Feel free to bookmark MindsDB's Github repository and give them a star.Engage with the MindsDB community on Slack or GitHub to ask questions and share your ideas and thoughts.

Not a programming language, but a database solution, called MindsDB. From the tab "How does MindsDB work?":

I picked a few of them on the hacktoberswag.com website. Precisely three: pusher.js, refine.dev, and MindsDB. You are probably asking Oh, you did not pick Wasp? The thing was, Wasp wasn’t listed on that web page and I didn’t know if any tool by that name existed.

MindsDB GitHub

The very first thing to do is to create your 30-day free to use Mindsdb account. Once this is done you are all set to explore and understand the MindsDB way of building machine learning models.

Check out https://github.com/mindsdb/mindsdb/ it's an ML project but has plenty of non-ML areas to contribute to. As well as a few no-code things too.

This is indeed the bread-and-butter, but there is use of all sorts of standard linear algebra algorithms. You can check various xla-related (accelerated linear algebra) folders in tensorflow or torch folders in pytorch to see the list of what is used [1],[2]

[1] https://github.com/tensorflow/tensorflow/tree/8d9b35f442045b...

[2] https://github.com/pytorch/pytorch/blob/6e3e3dd477e0fb9768ee...

2. TensorFlow Developed by the Google Brain team, TensorFlow is a powerful open-source machine learning framework that’s perfect for deep learning and neural network projects. With TensorFlow, you can build and train complex models using an intuitive and flexible API, making it an essential tool for any data scientist looking to delve into deep learning.

I found the official Tensorflow V1 code from a Github branch here (https://github.com/tensorflow/tensorflow/blob/r0.7/tensorflow/models/rnn/ptb/ptb_word_lm.py). All code necessary to run that file is in the /ptb folder (except data).

In their report they show the 10 projects with the biggest number of contributors. The first one is microsoft/vscode with 19.8K contributors in 2022 and the 10th place is tensorflow/tensorflow with 4.4K contributors. That's really nice, but my guess is that most repositories have very few contributors.

TensorFlow - This one needs no introduction. It’s widely-used and it has several tools and community resources for training and deploying ML/DL models. This one is JS based and I’m not too familiar with JS except that I know a lot of people use it for web development. What I like about it is that it’s used for speech and image recognition. And one of my favorites are text summarization.

If you mean StableHLO, then it has an MLIR dialect: https://github.com/openxla/stablehlo/blob/main/stablehlo/dia....

In the StableHLO spec, we are talking about this in more abstract terms - "StableHLO opset" - to be able to unambiguously reason about the semantics of StableHLO programs. However, in practice the StableHLO dialect is the primary implementation of the opset at the moment.

I wrote "primary implementation" because e.g. there is also ongoing work on adding StableHLO support to the TFLite flatbuffer schema: https://github.com/tensorflow/tensorflow/blob/master/tensorf.... Having an abstract notion of the StableHLO opset enables us to have a source of truth that all the implementations correspond to.

Install necessary dependencies: sudo apt-get update sudo apt-get upgrade sudo apt-get install build-essential git libhdf5-dev python-dev python-pip python-numpy python-wheel python-mock python-mockito python-pytest python-six python-h5py sudo pip install --upgrade pip sudo pip install setuptools Install Bazel: sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python wget https://github.com/bazelbuild/bazel/releases/download/0.26.1/bazel-0.26.1-installer-linux-x86_64.sh chmod +x bazel-0.26.1-installer-linux-x86_64.sh ./bazel-0.26.1-installer-linux-x86_64.sh --user Clone TensorFlow 1.x: git clone https://github.com/tensorflow/tensorflow.git cd tensorflow git checkout r1.15 Configure TensorFlow: ./configure Build TensorFlow: bazel build --config=opt --local_resources=1024,1.0,1.0 --verbose_failures //tensorflow/tools/pip_package:build_pip_package bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg sudo pip install /tmp/tensorflow_pkg/tensorflow-1.15.0-cp27-cp27mu-linux_armv7l.whl Set up swap memory: sudo fallocate -l 4G /swapfile sudo chmod 600 /swapfile sudo mkswap /swapfile sudo swapon /swapfile Test TensorFlow: python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"

Heck, I don't know how involved you feel like getting, but providing Python 3.11 support for tensorflow would be super awesome.

Uite ce scrie la limbaj aici: https://github.com/tensorflow/tensorflow