machine_learning_basics VS 100-Days-Of-ML-Code

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

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machine_learning_basics 100-Days-Of-ML-Code
5 3
4,205 43,302
- -
0.0 0.0
3 months ago 4 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.

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.

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.

What are some alternatives?

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

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

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:

mango - Parallel Hyperparameter Tuning in Python

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

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.

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

trulens - Evaluation and Tracking for LLM Experiments

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.)

rmi - A learned index structure

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

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

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