senapeksin/Miuul-MachineLearning
Data Science
This repository provides a structured learning path for individuals aiming to develop practical data science and machine learning skills. It guides you through handling raw datasets, preparing them for analysis, and building predictive models. You'll go from initial data exploration to constructing solutions for problems like sales forecasting or customer churn prediction.
No commits in the last 6 months.
Use this if you are an aspiring data scientist, analyst, or domain expert wanting to learn the end-to-end process of applying machine learning to real-world business problems using Python.
Not ideal if you are looking for a pre-built, ready-to-deploy software solution or a theoretical deep dive into advanced machine learning algorithms without practical application.
Stars
38
Forks
3
Language
Jupyter Notebook
License
—
Category
Last pushed
Aug 16, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/senapeksin/Miuul-MachineLearning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
rjurney/Agile_Data_Code_2
Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition
yogeshhk/TeachingDataScience
Course notes for Data Science related topics, prepared in LaTeX
linogaliana/python-datascientist
Dépôt associé au cours Python pour data scientists (ENSAE 2e année)
GoogleCloudPlatform/data-science-on-gcp
Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan,...
PacktWorkshops/The-Data-Science-Workshop
A New, Interactive Approach to Learning Data Science