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.

Data Career Handbook for all

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.

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.

Location information about commuter activities is vital for planning for travel disruptions and infrastructural development. The Mobility Sensing Project aims to find innovative and novel ways to identify travel patterns from GPS data and other multi-sensory data collected in smartphones. This will be transformative to provide personalised trave…

Predicting the incidents raised by the customer