100-Days-Of-ML-Code VS machine_learning_basics

Compare 100-Days-Of-ML-Code vs machine_learning_basics and see what are their differences.

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100-Days-Of-ML-Code machine_learning_basics
3 5
43,302 4,199
- -
0.0 0.0
4 months ago 3 months ago
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.

100-Days-Of-ML-Code

Posts with mentions or reviews of 100-Days-Of-ML-Code. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-07.

machine_learning_basics

Posts with mentions or reviews of machine_learning_basics. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-29.

What are some alternatives?

When comparing 100-Days-Of-ML-Code and machine_learning_basics you can also consider the following projects:

100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:

Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.

Data-science-best-resources - Carefully curated resource links for data science in one place

mango - Parallel Hyperparameter Tuning in Python

machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.

borb-google-colab-examples - This repository contains some examples of using borb in google colab. These examples enable you to try out the features of borb without installing it on your system. They also ensure the system requirements and imports are all taken care of.

dive-into-machine-learning - Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)

trulens - Evaluation and Tracking for LLM Experiments

100DaysOfCode - A GitHub Repo for my #100DaysOfCode challenge projects

rmi - A learned index structure

awesome-python-data-science - Probably the best curated list of data science software in Python.

PyImpetus - PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features