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Harish's Projects

-linear-regression-logistic-regression icon -linear-regression-logistic-regression

Linear Regression & Logistic RegressionLinear Regression & Logistic Regression Nov 2023 - Jan 2024Nov 2023 - Jan 2024 Restaurant Revenue Prediction (Python, Linear Regression): Developed a linear regression model to predict a restaurant's monthly revenue based on city population using Python

-predicting-and-understanding-viewer-engagement-with-educational-videos icon -predicting-and-understanding-viewer-engagement-with-educational-videos

Predicting and understanding viewer engagement with educational videosPredicting and understanding viewer engagement with educational videos Oct 2023 - Nov 2023Oct 2023 - Nov 2023 Video Engagement Prediction (Python, Machine Learning): Developed predictive models using educational video dataset with diverse properties like transcripts

awesome-python icon awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bert icon bert

TensorFlow code and pre-trained models for BERT

bike_demand_analysis icon bike_demand_analysis

Bike sharing systems are new generation of traditional bike rentals where whole process from membership, rental and return back has become automatic.

black_friday_sales_prediction icon black_friday_sales_prediction

This dataset comprises of sales transactions captured at a retail store. It’s a classic dataset to explore and expand your feature engineering skills and day to day understanding from multiple shopping experiences. This is a regression problem. The dataset has 550,069 rows and 12 columns.

breast_cancer_classification icon breast_cancer_classification

Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.

cheminformatics icon cheminformatics

Facilitates searching, screening, and organizing large chemical databases

code icon code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

credit_card_fraud_detection icon credit_card_fraud_detection

The dataset contains transactions made by credit cards in September 2013 by European cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.

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