DepHell
Metaflow
Activeeon
Luigi
Apache Airflow
Mesosphere DCOS
Kazuhm
Terraform
PyTorch
TensorFlow
Keras
Scikit-learn
OpenCV
CUDA
NumPy
Pandas
DepHell PyTorchNo DepHell videos yet. You could help us improve this page by suggesting one.
Based on our record, PyTorch seems to be a lot more popular than DepHell. While we know about 106 links to PyTorch, we've tracked only 4 mentions of DepHell. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I've found https://github.com/dephell/dephell but seems to be outdated. Source: over 1 year ago
I had a few relatively famous projects (like dephell), and at some point I lost my sleep because I was "fixing bugs" in it in my head in the middle of the night. Archiving it, closing issues in everything else, and starting to just write projects for my own fun only was the best decision I ever made. Don't make my mistakes. Don't ask random people on the internet what you should do. Do what you want to do and... Source: almost 2 years ago
You jest and yet... https://github.com/dephell/dephell Dephell is a converter for python packaging systems. It can turn poetry files into requirements.txt, or setuptools' setup.py into pipenv's Pipfile etc. Python Packaging: There is More Than One Way to Do It. - Source: Hacker News / over 2 years ago
Not necessarily. You can use Dephell (https://github.com/dephell/dephell) to convert from poetry to the old-fashioned requirements.txt. Source: about 3 years ago
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... - Source: dev.to / 21 days ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / about 2 months ago
Import torch # we use PyTorch: https://pytorch.org Data = torch.tensor(encode(text), dtype=torch.long) Print(data.shape, data.dtype) Print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this. - Source: dev.to / 3 months ago
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. - Source: dev.to / about 2 months ago
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. - Source: dev.to / about 2 months ago
Metaflow - Framework for real-life data science; build, improve, and operate end-to-end workflows.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Activeeon - ProActive Workflows & Scheduling is a java-based cross-platform workflow scheduler and resource manager that is able to run workflow tasks in multiple languages and multiple environments: Windows, Linux, Mac, Unix, etc.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.