ml-mipt VS pytorch-implementations

Compare ml-mipt vs pytorch-implementations and see what are their differences.

ml-mipt

Former repository of ML course. Redirect link included (by girafe-ai)
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ml-mipt pytorch-implementations
18 1
11 28
- -
0.0 0.0
over 2 years ago about 4 years ago
Jupyter Notebook Jupyter Notebook
MIT 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.

ml-mipt

Posts with mentions or reviews of ml-mipt. We have used some of these posts to build our list of alternatives and similar projects.

pytorch-implementations

Posts with mentions or reviews of pytorch-implementations. We have used some of these posts to build our list of alternatives and similar projects.
  • Paper Implementations using PyTorch
    1 project | /r/learnmachinelearning | 11 Jun 2021
    I have created a git repository that contains a collection of pytorch notebooks implementing different deep learning papers. These notebooks were created by me during my learning process and hopefully would help others play around with the concepts related to the papers. Here is the link: https://github.com/jaygala24/pytorch-implementations

What are some alternatives?

When comparing ml-mipt and pytorch-implementations you can also consider the following projects:

MachineLearningWithPython - Get started with Machine Learning with Python - An introduction with Python programming examples

ml-course - Open Machine Learning course

Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

paper-implementations - Attempts to implement various deep learning, computer vision papers.

mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.

conformal-prediction - Lightweight, useful implementation of conformal prediction on real data.

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Sevalla is the PaaS you have been looking for! Advanced deployment pipelines, usage-based pricing, preview apps, templates, human support by developers, and much more!
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InfluxDB – Built for High-Performance Time Series Workloads
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