data-science-notes VS machine_learning_complete

Compare data-science-notes vs machine_learning_complete and see what are their differences.

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data-science-notes machine_learning_complete
1 2
35 4,514
- -
0.0 5.9
over 1 year ago 8 months ago
Jupyter Notebook Jupyter Notebook
MIT License 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.

data-science-notes

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

machine_learning_complete

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

What are some alternatives?

When comparing data-science-notes and machine_learning_complete you can also consider the following projects:

MAPIE - A scikit-learn-compatible module for estimating prediction intervals.

embedding-encoder - Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.

hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

CardMap - Code to plot cardmarket orders on a map to show where my MtG cards ended up

Data-science - Collection of useful data science topics along with articles, videos, and code

event-transcripts - transcripts from our recorded events

60-Days-of-Data-Science-and-ML - 60 Days of Data Science and ML

PtitPrince - python version of raincloud

strava-analysis - 🏃📊 Using strava to do personal analyses and to practice data scientist skills.

Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.

linear_elasticity_3D_fenics - Finite element modeling for linear elasticity problem in 3D by using FEniCS software

artificial-intelligence - AI projects in python, mostly Jupyter notebooks.