Play-with-Machine-Learning-Algorithms VS pyprobml

Compare Play-with-Machine-Learning-Algorithms vs pyprobml and see what are their differences.

Play-with-Machine-Learning-Algorithms

Code of my MOOC Course <Play with Machine Learning Algorithms>. Updated contents and practices are also included. 我在慕课网上的课程《Python3 入门机器学习》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。 (by liuyubobobo)
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
Play-with-Machine-Learning-Algorithms pyprobml
15 3
1,241 6,257
- 1.7%
1.8 6.2
over 1 year ago 4 months 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.

Play-with-Machine-Learning-Algorithms

Posts with mentions or reviews of Play-with-Machine-Learning-Algorithms. We have used some of these posts to build our list of alternatives and similar projects.

pyprobml

Posts with mentions or reviews of pyprobml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-09.

What are some alternatives?

When comparing Play-with-Machine-Learning-Algorithms and pyprobml you can also consider the following projects:

RACplusplus - A high performance implementation of Reciprocal Agglomerative Clustering in C++

numpyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

jaxopt - Hardware accelerated, batchable and differentiable optimizers in JAX.

machine-learning-experiments - 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

lucid - A collection of infrastructure and tools for research in neural network interpretability.

PRML - PRML algorithms implemented in Python

lightwood - Lightwood is Legos for Machine Learning.

KoboldAI-Runpod - This is just a simple set of notebooks to load koboldAI and SillyTavern Extras on a runpod with Pytorch 2.0.1 Template

score_sde - Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

stable-diffusion-dreambooth-colab - Dreambooth for colab

MyST-NB - Parse and execute ipynb files in Sphinx