Rahul Samantara's repositories
Plant-app-UI
Plant Shop App UI in Flutter.
Ice-cream-parlour-app-UI
Ice Cream Parlour App UI in Flutter
Fitness-Trainer-App-UI
Fitness Trainer App built in Flutter
Minimalist-login-UI
Minimalist Login UI in Flutter
California-Housing-Data-Analysis_and-model-pred
The project aims at building a model of housing prices to predict median house values in California using the provided dataset. This model should learn from the data and be able to predict the median housing price in any district, given all the other metrics.
Customer-Service-Requests-Analysis
Performing a service request data analysis of New York City 311 calls. We will focus on the data wrangling techniques to understand the pattern in the data and also visualize the major complaint types.
Global-Warming-Chatbot
Chabot on Global Warming,
Webcam-Based-Motion-Detector
This is a Webcam Based Motion Detector created using Python, Open CV and Bokeh, capable of detecting motion and record time intervals to show.
flutter_ecommerce_app
E-Commerce App built in flutter
Geocoder-Application
This is a Geocoder Application made using Python, Flask and Pandas libraries.
github-readme-stats
:zap: Dynamically generated stats for your github readmes
imad-app-v2
Base repository for IMAD V2 course application. PLEASE DO NOT submit PRs, or push to this git repository!
Investigate-a-dataset_Tmdb_movies
In this project, I will analyze a dataset and then communicate my findings about it. I will use the Python libraries NumPy, pandas, and Matplotlib to make my analysis easier.
minimalist-flutter
Minimalist login in flutter
my-project-OVBD
This is a Project Repository Of My Project- "Online Volunteer Blood Donor" Website. This Website is built based on ASP.Net Framework & Bootstrap(Front-End) and SQL Server 2014 for Database. This is Website helps to find nearby volunteer donors and register for being volunteer donor.
Predict-Boston-housing-prices_-Udacity-ND-Project-
In this project, you will apply basic machine learning concepts on data collected for housing prices in the Boston, Massachusetts area to predict the selling price of a new home. You will first explore the data to obtain important features and descriptive statistics about the dataset. Next, you will properly split the data into testing and training subsets, and determine a suitable performance metric for this problem. You will then analyze performance graphs for a learning algorithm with varying parameters and training set sizes. This will enable you to pick the optimal model that best generalizes for unseen data. Finally, you will test this optimal model on a new sample and compare the predicted selling price to your statistics.
Test-a-Perceptual-Phenomenon
Udacity Data Analyst Nanodegree Term 2 Project1 Test a Perceptual Phenomenon