dex-lang VS Pytorch

Compare dex-lang vs Pytorch and see what are their differences.

dex-lang

Research language for array processing in the Haskell/ML family (by google-research)

Pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration (by pytorch)
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dex-lang Pytorch
25 353
1,563 80,652
0.9% 2.2%
8.2 10.0
2 months ago about 7 hours ago
Haskell Python
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

dex-lang

Posts with mentions or reviews of dex-lang. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-13.

Pytorch

Posts with mentions or reviews of Pytorch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-07-18.
  • Understanding AML/KYC: a light primer for engineers
    8 projects | dev.to | 18 Jul 2024
    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 Hugging Face Model Hub and Kaggle.
  • AMD to buy Finnish startup Silo AI for $665M in drive to compete with Nvidia
    2 projects | news.ycombinator.com | 10 Jul 2024
    pytorch already supports AMD with device=cuda

    already opensourced ROCm/HIP

    https://github.com/pytorch/pytorch/blob/fb8876069d89aaf27cc9...

  • The Programmer's Brain
    2 projects | news.ycombinator.com | 17 Jun 2024
    It's not just a problem when you are an amateur. This is sth that every project should provide.

    But there are also many projects which do. Sometimes you need to search a bit for it. Actually I would expect that most big projects have such documentation somewhere in some form.

    - https://github.com/WebKit/WebKit/blob/main/Introduction.md

    - https://www.chromium.org/developers/how-tos/getting-around-t...

    - https://github.com/pytorch/pytorch/blob/main/CONTRIBUTING.md...

    - https://returnn.readthedocs.io/en/latest/getting_started/tec...

    And then for some popular projects you will also find some independent overviews:

    - https://fabiensanglard.net/quake3/ (and many more on https://fabiensanglard.net/)

    - https://tldp.org/LDP/khg/HyperNews/get/tour/tour.html

    - https://realpython.com/cpython-source-code-guide/

    One problem is of course that those documents can be outdated and don't go into much details. But they still will give you important insights and should be a good starting point.

  • Essential Deep Learning Checklist: Best Practices Unveiled
    20 projects | dev.to | 17 Jun 2024
    How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include functionality to log predictions and consider parallel processing or GPU utilization for speed enhancements.
  • Mathematics secret behind AI on Digit Recognition
    3 projects | dev.to | 15 Jun 2024
    Hi everyone! I’m devloker, and today I’m excited to share a project I’ve been working on: a digit recognition system implemented using pure math functions in Python. This project aims to help beginners grasp the mathematics behind AI and digit recognition without relying on high-level libraries like TensorFlow or PyTorch. You can find the complete code on my GitHub repository.
  • Top 17 Fast-Growing Github Repo of 2024
    11 projects | dev.to | 14 Jun 2024
    PyTorch
  • AMD's MI300X Outperforms Nvidia's H100 for LLM Inference
    1 project | news.ycombinator.com | 13 Jun 2024
    > their own custom stack to interact with GPUs

    lol completely made up.

    are you conflating CUDA the platform with the C/C++ like language that people write into files that end with .cu? because while some people are indeed not writing .cu files, absolutely no one is skipping the rest of the "stack".

    source: i work at one of these "mega corps". hell if you don't believe me go look at how many CUDA kernels pytorch has https://github.com/pytorch/pytorch/tree/main/aten/src/ATen/n....

    > Everybody thinks it’s CUDA that makes Nvidia the dominant player.

    it 100% does

  • Awesome List
    25 projects | dev.to | 8 Jun 2024
    PyTorch - An open source machine learning framework. PyTorch Tutorials - Tutorials and documentation.
  • Understanding GPT: How To Implement a Simple GPT Model with PyTorch
    2 projects | dev.to | 31 May 2024
    In this guide, we provided a comprehensive, step-by-step explanation of how to implement a simple GPT (Generative Pre-trained Transformer) model using PyTorch. We walked through the process of creating a custom dataset, building the GPT model, training it, and generating text. This hands-on implementation demonstrates the fundamental concepts behind the GPT architecture and serves as a foundation for more complex applications. By following this guide, you now have a basic understanding of how to create, train, and utilize a simple GPT model. This knowledge equips you to experiment with different configurations, larger datasets, and additional techniques to enhance the model's performance and capabilities. The principles and techniques covered here will help you apply transformer models to various NLP tasks, unlocking the potential of deep learning in natural language understanding and generation. The methodologies presented align with the advancements in transformer models introduced by Vaswani et al. (2017), emphasizing the power of self-attention mechanisms in processing sequences of data more effectively than traditional approaches (Vaswani et al., 2017). This understanding opens pathways to explore and innovate in the field of natural language processing using cutting-edge deep learning techniques (Kingma & Ba, 2015).
  • Building a Simple Chatbot using GPT model - part 2
    1 project | dev.to | 31 May 2024
    PyTorch is a powerful and flexible deep learning framework that offers a rich set of features for building and training neural networks.

What are some alternatives?

When comparing dex-lang and Pytorch you can also consider the following projects:

jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Flux.jl - Relax! Flux is the ML library that doesn't make you tensor

futhark - :boom::computer::boom: A data-parallel functional programming language

mediapipe - Cross-platform, customizable ML solutions for live and streaming media.

julia - The Julia Programming Language

Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing

hasktorch - Tensors and neural networks in Haskell

flax - Flax is a neural network library for JAX that is designed for flexibility.

CIPs

tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]

tutorials - PyTorch tutorials.

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

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Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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Did you konow that Haskell is
the 23rd most popular programming language
based on number of metions?