Pytorch
Theano


Pytorch | Theano | |
---|---|---|
383 | - | |
86,719 | 9,913 | |
1.5% | 0.1% | |
10.0 | 5.0 | |
6 days ago | about 1 year ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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.
Pytorch
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10 Must-Have AI Tools to Supercharge Your Software Development
8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network design, training, and deployment in production environments. Download TensorFlow here and Download PyTorch here.
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Automating Enhanced Due Diligence in Regulated Applications
Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition.
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Must-Know 2025 Developer’s Roadmap and Key Programming Trends
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python, try projects that combine data with everyday problems. For example, build a simple recommendation system using Pandas and scikit-learn.
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Decorator JITs: Python as a DSL
Basically this style of code - https://github.com/pytorch-labs/attention-gym/pull/84/files - has issues like this - https://github.com/pytorch/pytorch/pull/137452 https://github.com/pytorch/pytorch/issues/144511 https://github.com/pytorch/pytorch/issues/145869
For some higher level context, see https://pytorch.org/blog/flexattention/
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Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis.
- PyTorch 2.6.0 Release
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Responsible Innovation: Open Source Best Practices for Sustainable AI
Open source frameworks like PyTorch are already enabling Machine Learning breakthroughs because they’re living communities where great things happen through:
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Golang Vs. Python Performance: Which Programming Language Is Better?
- Data Science and AI: TensorFlow, PyTorch and scikit-learn are only a few of the standard Python libraries. - Web Development: development of web-based applications is made simple by frameworks such as Flask as well as Django. - Prototyping: Python's ease of use lets you quickly iterate and testing concepts.
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How to resolve the dlopen problem with Nvidia and PyTorch or Tensorflow inside a virtual env
By chance, Tensorflow or PyTorch can work with pip packages from Nvidia.
- Making VLLM work on WSL2
Theano
We haven't tracked posts mentioning Theano yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️
neptune-client - 📘 The experiment tracker for foundation model training
tensorflow - An Open Source Machine Learning Framework for Everyone
Caffe2
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Caffe - Caffe: a fast open framework for deep learning.
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

