chdl17
Looking for new opportunities in the field of data science. Let's connect and discuss what I can contribute for your team.
United States
Pinned Repositories
activity-05-mini-competition
activity01-course-tools
activity02-slr
activity03-mlr
Bike-Sharing
MotorCycle sharing is a machine learning case study used to predict the demand for bikes in certain areas. It involves predicting the number of bikes available at a given time, and then adjusting the supply accordingly. Data such as weather, time of day, and the number of bikes already in use are used to make the predictions.
Comment-Toxicity
Project is all about build a deep learning model to identify toxic comments
Credit-EDA-CaseStudy
Credit EDA is a GitHub repository designed to provide educational materials and tools for exploring credit risk data. The repository contains notebooks, datasets, and code samples to help users learn and apply these concepts to credit data.
IPL_Analysis_R
This GitHub repository contains R code for analyzing Indian Premier League (IPL) data. The repository also includes a detailed report explaining the results and insights gained from the analysis. It is a great resource for anyone interested in understanding the performance of teams and players in the IPL using data science tools.
NYC_Green_Taxis_Peak_Hour_Analysis
This project analyzes GCP BigQuery data and uses Looker Studio to build a Peak Hour Analysis.
ToDo-App-Backend-with-FastAPI-
The ToDo API Project is a RESTful API built using FastAPI and SQLAlchemy. It provides CRUD operations for managing ToDo items, using an SQLite database for storage. This project showcases how to implement a simple and efficient task management system with modern Python tools. Perfect for learning FastAPI, SQLAlchemy, and building scalable APIs.
chdl17's Repositories
chdl17/activity-05-mini-competition
chdl17/activity01-course-tools
chdl17/activity02-slr
chdl17/activity03-mlr
chdl17/activity04-regression-considerations
chdl17/Bike-Sharing
MotorCycle sharing is a machine learning case study used to predict the demand for bikes in certain areas. It involves predicting the number of bikes available at a given time, and then adjusting the supply accordingly. Data such as weather, time of day, and the number of bikes already in use are used to make the predictions.
chdl17/Comment-Toxicity
Project is all about build a deep learning model to identify toxic comments
chdl17/Credit-EDA-CaseStudy
Credit EDA is a GitHub repository designed to provide educational materials and tools for exploring credit risk data. The repository contains notebooks, datasets, and code samples to help users learn and apply these concepts to credit data.
chdl17/Google-Play-Store-Reviews
This is the repository for the Data Engineering Project done in Azure Databricks
chdl17/IPL_Analysis_R
This GitHub repository contains R code for analyzing Indian Premier League (IPL) data. The repository also includes a detailed report explaining the results and insights gained from the analysis. It is a great resource for anyone interested in understanding the performance of teams and players in the IPL using data science tools.
chdl17/NYC_Green_Taxis_Peak_Hour_Analysis
This project analyzes GCP BigQuery data and uses Looker Studio to build a Peak Hour Analysis.
chdl17/Olympics-DE-Project
This is the repository for the Data Engineering Project in Azure
chdl17/ToDo-App-Backend-with-FastAPI-
The ToDo API Project is a RESTful API built using FastAPI and SQLAlchemy. It provides CRUD operations for managing ToDo items, using an SQLite database for storage. This project showcases how to implement a simple and efficient task management system with modern Python tools. Perfect for learning FastAPI, SQLAlchemy, and building scalable APIs.
chdl17/activity06-logistic-regression
chdl17/activity07-discriminant-analysis
chdl17/activity08-mini-competition
chdl17/activity09-bootstrapping
chdl17/chdl17
chdl17/chdl17.github.io
My Portfolio
chdl17/IMDB-Assignment
This GitHub repository contains a project that performs an analysis of the IMDb movie rating dataset. The data is used to explore the relationships between various features and the movie rating. Visualizations are used to illustrate the results of the analysis. The code is organized into a Jupyter Notebook file and data files.
chdl17/Lead-Score-Case-Study
Lead scoring is the process of assigning a numerical value or score to each lead, based on factors such as demographics and behavior, to determine their potential value as customers.
chdl17/MarvelVsDC
This GitHub repository contains Python and Tableau for analyzing Marvel Vs DC superheros.
chdl17/NewChic_Retail
This GitHub repository contains R code for analyzing retail analysis with the count dependent variable.
chdl17/URL-HTTP-Requests
How to use Request in python to fetch data from URL