ai-computation-and-hardware-trends-analytics
This repository contains a comprehensive Jupyter notebook that provides in-depth analysis on various aspects of artificial intelligence, including computation, training, corporate investments, and market share in logic chip production.
View Projectai-ml-popularity-analysis
This repository contains a comprehensive analysis of global trends in AI and ML popularity, including data preprocessing, EDA, PCA, clustering, time series, and statistical analysis.
View Projectamazon-product-availablity-checker
It is an Amazon product availability checker made using Python.
View Projectanomaly-detection-system
This repository contains a real-time anomaly detection system designed to monitor and detect anomalies such as unauthorized access, violence, or unusual activities using a webcam feed. The system leverages OpenCV for video processing, YOLO (You Only Look Once) for object detection, and a custom anomaly detection model built with PyTorch.
View Projectauto-clicker
An auto clicker using Python involves simulating mouse clicks at specific positions on the screen
View ProjectBechdel_IMDB_dataset_analysis
This repository explores various aspects of movies through a series of Jupyter notebooks, analyzing trends in women's representation based on Bechdel test scores and IMDb ratings. It includes studies on genre differences, budget impacts, box office performance, and the influence of director and writer gender on women's representation in films.
View Projectbike-sharing-analysis
This repository contains analysis of daily bike rentals using data preprocessing, exploratory data analysis, and visualizations. Includes a linear regression model to predict rentals based on weather conditions.
View ProjectBrain-Tumor-Detection
This repository contains a project that leverages deep learning techniques to automate the detection of brain tumors from MRI images. Using a Convolutional Neural Network (CNN), the model is trained to classify MRI images into two categories: images with brain tumors and images without brain tumors.
View ProjectBreast-Cancer-Analysis
This repository contains a comprehensive analysis of the Breast Cancer dataset, including data cleaning, exploratory data analysis (EDA), feature engineering, model development, and evaluation. This project aims to develop predictive models and treatment protocols to improve breast cancer management and patient outcomes.
View Projectchatgpt-reviews-analysis
This repository contains an in-depth analysis of ChatGPT Android App user reviews, including sentiment analysis, temporal trends, score distribution, and thumbs up analysis, to gain insights into user feedback and improve the app experience.
View Projectcifar10-resnet-classification
This project focuses on classifying images from the CIFAR-10 dataset using a Residual Network (ResNet) architecture. The CIFAR-10 dataset consists of 60,000 32x32 color images in 10 classes, such as airplanes, automobiles, birds, cats, deer, dogs, frogs, horses, ships, and trucks.
View Projectconversations-analysis
This repository contains an in-depth analysis of the OpenLeecher/GPT4-10k dataset, featuring 100 conversations on coding, debugging, storytelling, and science. Utilizes NLP techniques for sentiment analysis, entity recognition, clustering, and summarization to uncover key themes and insights for conversational AI and NLP research.
View ProjectCRED_Analysis
This repository focuses on the analysis of the Crowd Reaction Estimation Dataset (CRED), which contains pairs of tweets from The White House with comparative measures of retweet counts. The goal of this analysis is to gain insights into tweet engagement and the factors influencing retweet counts.
View Projectcustomer-segmentation-analysis
This repository contains a comprehensive analysis of customer data to identify distinct segments for targeted marketing, improved satisfaction, and increased sales. Includes data preprocessing, exploratory data analysis, KMeans clustering, and segment profiling. Technologies: Python, pandas, numpy, matplotlib, seaborn, scikit-learn.
View Projectcyber-security-analysis
This repository features an in-depth analysis of a refined cyber security attacks dataset. It includes exploratory data analysis, correlation analysis, clustering, predictive modeling, anomaly detection, and advanced techniques to uncover insights and patterns, aiding in the development of effective cyber security strategies.
View ProjectData-Developer-Salaries-2024
This repository contains a comprehensive analysis of the 2024 data developer salaries and employment attributes, including salary distribution, job titles, experience levels, employment types, remote work, and company size. Gain insights into trends and patterns in the field.
View Projectdata-structures-and-algorithms
Complete DSA Course - Basics to Advance with concepts, visualization and Interview questions
View ProjectDomestic-Violence-Analysis
This repository contains an in-depth analysis of domestic violence against women in a specific rural area of a developing country. The goal is to understand the correlation between various socio-economic factors and domestic violence, providing insights for effective interventions and policies.
View Projectdsa-notes
This repo contains the notes of different data structures and important questions which would help in acing interview rounds.
View Projectfastag-fraud-analyis
This repository contains a Jupyter Notebook for a comprehensive analysis of Fastag fraud data from India's electronic toll collection system. The project aims to detect fraudulent transactions using machine learning techniques.
View Projectfictional-character-battle-analysis
This repository features a comprehensive analysis of fictional character battle outcomes from Marvel and DC Comics. Using attributes like strength, speed, and special abilities, we predict battle results with machine learning models. The detailed Jupyter Notebook includes data preprocessing, modeling, and scenario simulations.
View Projectfootball-teams-valuation-analysis
This repository contains a comprehensive analysis of football team valuations using a dataset with features influencing the financial valuation of football teams across major European leagues. The project involves comprehensive data cleaning, exploratory data analysis (EDA), feature engineering, and advanced machine learning modeling.
View Projectforage-jpmc-swe-task-1
Starter repo for task 1 of the JPMC software engineering program
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