simple linear regression assignment
Time series forecasting of coal prices (2020-2024) using ARIMA, LSTM, GRU, and XGBoost, with Power BI dashboarding.
Explored different attributes of Boston housing dataset then a part of dataset was used to train the linear regression algorithm after that trained model was used to give predictions on remaining part of dataset.
End-to-end Python data analysis pipeline tracking global data job vacancies, market skill trends, and salary distributions
Explore Diwali Sales Data Analysis: a project dissecting 11,251 records with 15 columns to uncover customer demographics and buying trends during the festive season. The objective? Understand customer behavior, identify key demographics and product categories driving sales. Utilizing Python libraries like Pandas, NumPy, Matplotlib, and Seaborn, thi
Cartoonify images using opencv and tkinter
Files from the group repository were shifted to this repository. This project uses Python and its modules to perform analyze a dataset, and present them using Tableau.
The Diwali sales analysis reviews past data to identify trends, peak buying times, popular products, and customer demographics. It assesses sales volume, revenue growth, and promotional effectiveness, helping businesses optimize marketing and inventory for future seasons.
This directory includes the demonstration of data analysis using basic of NumPy, pandas for analysis and matplotlib for visualization
Exploratory data analysis case study focused on hotel booking behavior and cancellation trends. The analysis was performed using Python in Jupyter Notebook to uncover factors influencing hotel booking cancellations, customer behavior, seasonal demand, and revenue-related patterns.
A Streamlit web app that analyzes WhatsApp chat data to provide insights on user activity, message trends, emojis, and word usage through interactive visualizations.
This project implements a handwritten digit detector using machine learning.
Streamlit NLP app using transformer models for emotion detection, journaling, and insights.
A data-driven system to assist farmers in selecting the right crop for given conditions.
🌸 Iris Flower Classification using KNN and Streamlit | Machine Learning project for predicting Iris species with interactive visualizations.
Analyze Diwali sales trends using Python (Pandas, Seaborn, Matplotlib and numpy ). This project performs EDA on customer demographics, geography, and product categories to uncover key purchasing patterns and provide actionable insights for retail business optimization.
Implementation of Simple and Multiple Linear Regression using Scikit-learn with data preprocessing, model training, evaluation metrics, and visualization.
A Python data analysis pipeline that cleans a year of e-commerce transaction data, answers key business questions, and produces a client-ready Excel report with charts.
A/B-тест обновлённого онбординга в финтех-приложении: проверка гипотез
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