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PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...

PyTorch Reviews and details

Screenshots and images

  • PyTorch Landing page
    Landing page //
    2023-07-15

Features & Specs

  1. Dynamic Computation Graph

    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.

  2. Pythonic Nature

    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.

  3. Strong Community Support

    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.

  4. Flexibility and Control

    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.

  5. Support for GPU Acceleration

    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.

  6. Rich Ecosystem

    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

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Videos

PyTorch in 5 Minutes

Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips

PyTorch at Tesla - Andrej Karpathy, Tesla

Social recommendations and mentions

We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about PyTorch and what they use it for.
  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 2 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 16 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 1 month ago
  • 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... - Source: dev.to / 3 months ago
  • 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. - Source: dev.to / 3 months ago
  • 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,... - Source: dev.to / 3 months ago
  • 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. - Source: dev.to / 3 months ago
  • 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:. - Source: dev.to / 4 months ago
  • 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. - Source: dev.to / 4 months ago
  • 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. - Source: dev.to / 4 months ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 5 months ago
  • Understanding the MLOps Lifecycle
    Popular tools for model development are TensorFlow, MLFlow, and PyTorch. - Source: dev.to / 5 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Torch: For model inference and tensor operations. - Source: dev.to / 5 months ago
  • Top 8 OpenSource Tools for AI Startups
    For those who prefer a more flexible, Pythonic interface, PyTorch is often the way to go. Its dynamic computation graphs and ease of use have made it a favorite for researchers and AI startups alike. Plus, the thriving PyTorch community means plenty of support and open-source examples. - Source: dev.to / 7 months ago
  • JAX vs PyTorch: Comparing Two Powerhouses in ML Frameworks
    Developed by the Facebook AI Research (FAIR) lab, PyTorch is an open-source machine learning framework used to build efficient machine learning models. In contrast to JAX, PyTorch is based on an imperative programming paradigm. It is a popular library and is used by many companies to build their machine learning models. - Source: dev.to / 7 months ago
  • Is Open Source AI Bull?
    Software Frameworks. These are the libraries and frameworks on which the system source code is built. One needs access to not only the frameworks (many of these are open source software already, such as PyTorch and Tensorflow) but also the specific versioning used in the system source code and the training source code. Details matter. - Source: dev.to / 7 months ago
  • Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
    PyTorch is a tool for building deep learning models, launched by Meta in 2016. It is often used in image recognition, natural language processing, and reinforcement learning. PyTorch is essential for researchers, data scientists, and machine learning engineers. - Source: dev.to / 7 months ago
  • How to Learn Generative AI: A Step-by-Step Guide
    Use TensorFlow and PyTorch to experiment with building neural networks. - Source: dev.to / 8 months ago
  • The 6 Best LLM Tools To Run Models Locally
    Import Models: Ollama supports importing models from PyTorch. - Source: dev.to / 9 months ago
  • Building and Training a Neural Network with PyTorch: A Step-by-Step Guide
    In this guide, we’ll embark on a journey to build and train a neural network using PyTorch. We’ll start by preparing our data — transforming raw images into a format suitable for training our model. Then, we’ll delve into defining our neural network architecture, which will learn to recognize various clothing items based on their pixel patterns. For this project we will use FashionMNIST dataset. - Source: dev.to / 10 months ago
  • Understanding AML/KYC: a light primer for engineers
    Machine learning techniques empower automated systems to detect and learn patterns and anomalies across enormous datasets, optimizing the accuracy of fraud detection. Libraries like TensorFlow or PyTorch are extensively used to build predictive models that can identify suspicious transaction patterns, enhancing the effectiveness of your AML/KYC processes. You can find publicly available models on sites like... - Source: dev.to / 10 months ago

External sources with reviews and comparisons of PyTorch

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for developers to experiment with different deep...
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of the water. Almost 85% of models are...
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice versa.

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PyTorch discussion

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  1. User avatar
    ldenoue
    · over 1 year ago
    · Reply

    PyTorch is just the best developer experience for developing AI stacks.

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