A list of compatible datasets, noting other major repositories containing popular real-world datasets, along with sample code for a range of recommendation tasks.

NBA History & analysis of: Player of the week, Head coaches, players statistics per season

This repository contains my machine learning models implementation code using streamlit in the Python programming language.

Kaggle Dataset Participation Code

Movie Recommender System is the python Based Project To Create Content Based Recommender System using TMDB 5000 movie dataset from Kaggle

Computer hardware performance which has been recorded and is open for free usage. Licensed under the MIT License & CC-BY-4.

This is my first project on Github

This repository contains programs in the Python programming language using Module Streamlit.

This project allows users to thoroughly test their HuggingFace AI models with comparison and saving functionalities.

Feature engineering for INGV data

This repository contains machine learning programs in the Python programming language.

Statistical data analysis report on Kaggle dataset Student Performance made as a personal project.

A solution for identifying and recognizing landmarks from images, addressing key challenges and leveraging both algorithmic and human expertise to achieve high accuracy and reliability.

An initial phase segmentation using LinkNet on the skin lesion dataset managed by VISION AND IMAGE PROCESSING LAB, University of Waterloo. Public dataset on Kaggle at https://www.kaggle.com/datasets/mahmudulhasantasin/university-of-waterloo-skin-cancer-db-80-10-10/.

In-depth analysis of NYC Yellow Taxi data, exploring trip patterns, fare amounts, demand hotspots, and correlations using PySpark and Databricks.

Exploratory Data Analysis and Random Forest Survival Prediction

This repository contains notebooks in which I have implemented ML Kaggle Exercises for academic and self-learning purposes. In my notebooks, I have implemented some basic processes involved in ML Data Processing like How to take care of Missing Values, Handling Categorical Variables, and operations like mapping, 'Grouping', 'Sorting', 'Renaming …

This Series contains Data Analysis projects performed on different Kaggle datasets and providing valuable insights into the data by making use of Python libraries.

AniSearchModel leverages Sentence-BERT (SBERT) models to generate embeddings for synopses, enabling the calculation of semantic similarities between descriptions. This allows users to find the most similar anime or manga based on a given description.