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ames-housing-price-analysis

In this project, we'll be conducting an exploratory data analysis of housing prices data. Our goal is to understand the key factors that influence the prices of homes and identify any patterns in the data.

credit-card-approval-prediction

credit-card-fraud-detection-ml

This project involves using machine learning techniques to build a predictive model for detecting fraudulent credit card transactions.

customer-churn-prediction

This project leverages ML algorithms to predict and tackle customer churn effectively.

dlt

data load tool (dlt) is an open source Python library that makes data loading easy 🛠️

ethereum-etl-airflow

Airflow DAGs for exporting, loading, and parsing the Ethereum blockchain data. How to get any Ethereum smart contract into BigQuery https://towardsdatascience.com/how-to-get-any-ethereum-smart-contract-into-bigquery-in-8-mins-bab5db1fdeee

king-county-house-sales-analysis

microsoft-movie-studio-eda

movie-recommendation-system

online-food-delivery-profitability-analysis

This repository contains an in-depth analysis of the profitability factors in the online food delivery industry. The analysis encompasses various aspects such as delivery costs, menu pricing strategies, customer preferences, and revenue optimization techniques.

oreilly_intermediate_sql_for_data

Resources for the O'Reilly Online Training "Intermediate SQL For Data Analysis"

pandas_exercises

Practice your pandas skills!

real-time-etl-pipeline

Real-Time-ETL-Pipeline is a repository containing an example of a real-time ETL (Extract, Transform, Load) pipeline implemented using Apache Airflow. The pipeline scrapes data from a website, transforms it, and loads it into a CSV file.

spotify-api

threads-reviews-sentiment-analysis

This repository is dedicated to the sentiment analysis of reviews from Threads, a platform for sharing thoughts and opinions on various topics. Using natural language processing (NLP) techniques, the analysis delves into the sentiment expressed in user reviews to uncover insights and trends.