Welcome to the Multiverse of Data Science — a comprehensive, ever-expanding collection of over 100 real-world projects covering the entire data science pipeline!
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Updated
Jul 22, 2025 - Jupyter Notebook
Welcome to the Multiverse of Data Science — a comprehensive, ever-expanding collection of over 100 real-world projects covering the entire data science pipeline!
Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.
Data science, machine learning books and resources
Командный репозиторий.
70+ DataCamp Course Notes, Projects, Codes, Exercises on Python, R and SQL with full DS & ML Certification,
This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price
This Repository contains the real life use cases of GenAI (LLM+RAG) in Finance Domain. I covers many projects use cases with theory and projects.
a tool for comparing the predictions of any text classifiers
Ethereum Fraud Detection Models
This Repo contains tools that allow us to import, clean, manipulate, and visualize data —Includes Python libraries, like pandas, NumPy, Matplotlib, and many more to work with real-world datasets to learn the statistical and machine learning techniques.
Demonstrating the efficiency of pmdarima’s auto_arima() function compared to implementing a traditional ARIMA model.
Все о машинном обучении и не только...
A credit scoring web app based on an ML model trained on relevant data.
The dataset builder script extracts the most relevant market data straight from Binance's API and builds a series of datasets that can be used in data science and machine learning projects.
Data Career Handbook for all
A list of Incomplete Interview Questions (Python and Data Science only )
Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python
This project uses supervised machine learning techniques with multiple regression models to predict CO2 emissions in Canada, it includes data cleaning, encoding, analyzing and visualization to identify patterns, resulting in a model that can make accurate predictions.
Predicting the incidents raised by the customer
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