Rahul Gupta's repositories
Machinehack-Power-Plant-Energy-Output-Prediction
The dataset was collected from a Combined Cycle Power Plant over 6 years (2006-2011) when the power plant was set to work with a full load. Features consist of hourly average ambient variables Temperature (T), Ambient Pressure (AP), Relative Humidity (RH), and Exhaust Vacuum (V) to predict the net hourly electrical energy output (PE) of the plant.
MachineHack-metalfurnace-classification
Metal Furnace Challenge : Weekend Hackathon #1. Given are 28 distinguishing factors in the manufacturing of an alloy, your objective as a data scientist is to build a Machine Learning model that can predict the grade of the product using these factors.
COVID-19-data-visualization-and-time-series-analysis-with-animated-charts-using-plotly-on-Kaggle
COVID 19 data visualization and time series analysis with animated charts using plotly.
Machinehack-Cardiac-Risk-Prediction
Plugin Hackathon : Cardiac Arrest Risk Prediction. Your objective as a data scientist is to build a machine learning model that can predict if a patient is likely to have a cardiac arrest or not.
Machinehack-E-Commerce-product-price-prediction
E-commerce Price Prediction: Weekend Hackathon #8. Given are 7 distinguishing factors that can influence the price of a product on an e-commerce platform. Your objective as a data scientist is to build a machine learning model that can accurately predict the price of a product based on the given factors.
Machinehack-Financial-Risk-Prediction
Machinehack Financial Risk prediction. Given are 7 distinguishing factors that can provide insight into whether an organization may face a financial risk or not. Your objective as a data scientist is to build a machine learning model that can predict if an organization will fall under the risk using the given features.
Pyspark-Theory-and-Code-Basics
Pyspark serves as a Python interface to Apache Spark, enabling the execution of Python and SQL-like instructions for the manipulation and analysis of data within a distributed processing framework.
Analytics-Vidhya-Janta-Hack-Demand-Forecasting
Analytics Vidhya JanataHack Demand Forecasting hackathon. One of the largest retail chains in the world wants to use their vast data source to build an efficient forecasting model to predict the sales for each SKU in its portfolio at its 76 different stores using historical sales data for the past 3 years on a week-on-week basis.
Dockship-AI-challenges
Dockship.io is a developer community where we host online Challenges for developers to skill up, earn money and to get hired.
HackerEarth-Machine-Learning-Challenge-Carnival-Wars
Halloween is a night of costumes, fun, and candy that takes place every year on October 31. On this day people dress up in various costumes that have a scary overtone and go trick-or-treating to gather candy. This year, on Halloween, there is a carnival in your neighborhood. Besides the various games, there are also 50 stalls that are selling various products, which fall under various categories. Your task is to predict the selling price of the products based on the provided features.
Real-Time-Cryptocurrency-Data-Collection-and-Dashboarding
This project focuses on data ingestion, ETL (Extract, Transform, Load), and dashboarding for cryptocurrency data. Utilizing Python and Google Cloud Platform (GCP) tools such as BigQuery, Looker, and Compute Engine, I have built a seamless data pipeline and insightful dashboards.
Leetcode-DataLemur-Solutions
Leetcode & DataLemur solutions
Machinehack-Forest-Cover-Classification
Machinehack Forest Cover Classification weekend hackathon 12. The dataset is taken from UCI. This study area includes four wilderness areas located in the Roosevelt National Forest of northern Colorado.
MachineHack-Glass-Quality-Prediction
Glass Quality Prediction : Weekend Hackathon #6. Given are 15 distinguishing factors that can provide insight into what grade of the glass is being produced. Your objective as a data scientist is to build a machine learning model that can predict the grade of glass based on the given factors.
MachineHack-Insurance-Churn-Prediction-
Insurance Churn Prediction : Weekend Hackathon #2. Given are 16 distinguishing factors that can help in understanding the customer churn, your objective as a data scientist is to build a Machine Learning model that can predict whether the insurance company will lose a customer or not using these factors.
Machinehack-Message-polarity-prediction
Message Polarity Prediction : Weekend Hackathon #3. Given are 53 distinguishing factors that can help in understanding the polarity(Good or Bad) of a message, your objective as a data scientist is to build a Machine Learning model that can predict whether a text message has brought you good news or bad news.
Machinehack-ODI-Match-Winner-hackathon
Predict ODI Match Winner : Weekend Hackathon #9. Given are 7 distinguishing factors that can influence the price of a product on an e-commerce platform. Your objective as a data scientist is to build a machine learning model that can accurately predict the price of a product based on the given factors.
Machinehack-Video-Game-Sales-Prediction
Video Game Sales Prediction: Weekend Hackathon 10. Given are 8 distinguishing factors that can influence the sales of a video game. Your objective as a data scientist is to build a machine learning model that can accurately predict the sales in millions of units for a given game.
Python-GUI-and-Serial-Communication-using-PyQt5
IOT based live tracing and tracking using Python3 and Serial Communication via microcontrollers
Zindi-Mobile-Banking-Prediction-Challenge
Banks and financial service providers value knowing what habits their clients follow. This allows them to tailor products and services. This challenge asks you to build a machine learning model to predict if individuals across Africa and around the world use mobile or internet banking.