PyTorch-NLP VS tutorials

Compare PyTorch-NLP vs tutorials and see what are their differences.

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PyTorch-NLP tutorials
1 30
2,180 7,790
- 1.9%
0.0 9.4
10 months ago 7 days ago
Python Jupyter Notebook
BSD 3-clause "New" or "Revised" License BSD 3-clause "New" or "Revised" License
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.

PyTorch-NLP

Posts with mentions or reviews of PyTorch-NLP. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-02.

tutorials

Posts with mentions or reviews of tutorials. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-09-19.
  • Ask HN: Is there a tutorial avaible for Deep Learning based Upscaling
    1 project | news.ycombinator.com | 10 Mar 2024
    There are plenty of tutorials for Deep Learning available, https://pytorch.org/tutorials/. Does anyone know of a tutorial or example of Image Upscaling in a similar vain to Nvidia's DLSS?
  • Best Portfolio Projects for Data Science
    3 projects | dev.to | 19 Sep 2023
    Pytorch Documentation
  • unique game idea ( literally )
    1 project | /r/GameDevelopment | 4 Sep 2023
    PyTorch: https://pytorch.org/tutorials/
  • How to learn PyTorch?
    1 project | /r/learnmachinelearning | 14 Jun 2023
    There's a TON of tutorials in the pytorch tutorials section, they're pretty solid. If you know what area you're specifically interested in, check to see if you can find some relevant tutorials to start with.
  • What are some good pytorch courses online?
    1 project | /r/learnpython | 16 May 2023
  • How do I get started with ML?
    2 projects | /r/ChatGPT | 17 Mar 2023
    Learn Python: Python is the most popular language for ML and AI projects. Start by learning the basics of Python, then move on to more advanced topics. Some great resources for learning Python include: Codecademy's Python course: https://www.codecademy.com/learn/learn-python Real Python: https://realpython.com/ Mathematics: A solid understanding of mathematics, particularly linear algebra, calculus, probability, and statistics, is essential for ML. Here are some resources to help you learn: Khan Academy courses: Linear Algebra: https://www.khanacademy.org/math/linear-algebra Calculus: https://www.khanacademy.org/math/calculus-1 Probability and Statistics: https://www.khanacademy.org/math/statistics-probability 3Blue1Brown's YouTube series on Linear Algebra: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Data processing and manipulation: Familiarize yourself with popular Python libraries for data manipulation and analysis, such as NumPy, pandas, and matplotlib: NumPy: https://numpy.org/doc/stable/user/quickstart.html pandas: https://pandas.pydata.org/pandas-docs/stable/getting_started/intro_tutorials/index.html matplotlib: https://matplotlib.org/stable/tutorials/index.html Machine learning concepts: Learn about the basic concepts of ML, including supervised learning, unsupervised learning, and reinforcement learning. Some great resources include: Coursera's Machine Learning course by Andrew Ng: https://www.coursera.org/learn/machine-learning Google's Machine Learning Crash Course: https://developers.google.com/machine-learning/crash-course Fast.ai's Practical Deep Learning for Coders course: https://course.fast.ai/ Deep learning libraries: Get familiar with popular deep learning libraries such as TensorFlow and PyTorch: TensorFlow: https://www.tensorflow.org/tutorials PyTorch: https://pytorch.org/tutorials/ Specialize and work on projects: Choose an area of interest (such as natural language processing, computer vision, or reinforcement learning), and start working on projects to apply your skills. You can find datasets and project ideas from sources like: Kaggle: https://www.kaggle.com/ Papers With Code: https://paperswithcode.com/ Stay up-to-date and join the community: Follow ML blogs, podcasts, and conferences to stay current with the latest developments. Join ML communities and forums like r/MachineLearning on Reddit, AI Stack Exchange, or specialized Discord and Slack groups.
  • How do I activate the TPU when using pytorch (code inside)?
    1 project | /r/kaggle | 12 Dec 2022
    The code looks almost identical to this: https://github.com/pytorch/tutorials/blob/master/beginner_source/chatbot_tutorial.py
  • How to Implement Feed Forward NN in PyTorch for Classification
    1 project | /r/datascience | 24 Nov 2022
    Well the pytorch documentation is pretty good. (https://pytorch.org/tutorials/)
  • PyTorch Tutorial for People with Keras/Tensorflow experience?
    1 project | /r/learnmachinelearning | 28 Oct 2022
    Pytorch tutorials https://pytorch.org/tutorials/ on their official website has all the basic commands and should be easier to pickup since you already know tensorflow/ keras.
  • PyTorch introduces ‘nvFuser’: a Deep Learning Compiler for NVIDIA GPUs that automatically just-in-time compiles fast and flexible kernels to reliably accelerate users’ networks
    1 project | /r/artificial | 29 Aug 2022
    Continue reading |Github link | Reference article

What are some alternatives?

When comparing PyTorch-NLP and tutorials you can also consider the following projects:

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

dex-lang - Research language for array processing in the Haskell/ML family

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

NLTK - NLTK Source

FlexFlow - FlexFlow Serve: Low-Latency, High-Performance LLM Serving

pytext - A natural language modeling framework based on PyTorch

adaptdl - Resource-adaptive cluster scheduler for deep learning training.

Jieba - 结巴中文分词

pytorch-lightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. [Moved to: https://github.com/PyTorchLightning/pytorch-lightning]

Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

pytorch_geometric - Graph Neural Network Library for PyTorch [Moved to: https://github.com/pyg-team/pytorch_geometric]