unnatibshah
Master's in Computer Science @ USC. Data Science | Machine Learning | Artificial Intelligence | NLP | Software Development
University of Southern CaliforniaCalifornia
Pinned Repositories
Address-book
Addressbook
Address Book in Python
Archery-game
Computer Graphics: Archery Game
clustering_geolocation_data
COVID-19-DATA-EXPLORATION
EDA in Python based on the data acquired from ’ourworldindata.org’.
CSCI544-NLP
CSCI 544 - Applied Natural Language Processing (Spring 2023) | Graduate Level Course taught by Prof. Mohammad Rostami, Xuezhe Ma at USC | Credits - 4
Fake-News-Detection
In this project, we leveraged the LIAR dataset, which contains real-life political statements, to identify instances of fake news.
Image-Caption-Generator
This is a Python-based deep learning project that leverages Convolutional Neural Networks and LTSM (a type of Recurrent Neural Network) to build a deep learning model that can generate captions for an image.
LASSO-and-Boosting-for-Regression
LASSO and Boosting for Regression on Communities and Crime data
Powered-by-Sun
Leveraging Machine Learning to Forecast the Throughput of Solar Power along with Cost and Size Calculation.
unnatibshah's Repositories
unnatibshah/Address-book
unnatibshah/CSCI544-NLP
CSCI 544 - Applied Natural Language Processing (Spring 2023) | Graduate Level Course taught by Prof. Mohammad Rostami, Xuezhe Ma at USC | Credits - 4
unnatibshah/LASSO-and-Boosting-for-Regression
LASSO and Boosting for Regression on Communities and Crime data
unnatibshah/Addressbook
Address Book in Python
unnatibshah/Archery-game
Computer Graphics: Archery Game
unnatibshah/clustering_geolocation_data
unnatibshah/COVID-19-DATA-EXPLORATION
EDA in Python based on the data acquired from ’ourworldindata.org’.
unnatibshah/Crowd-Counting-using-Deep-Learning
unnatibshah/Detecting-Covid19-with-Chest-X-Ray
unnatibshah/Fake-News-Detection
In this project, we leveraged the LIAR dataset, which contains real-life political statements, to identify instances of fake news.
unnatibshah/Image-Caption-Generator
This is a Python-based deep learning project that leverages Convolutional Neural Networks and LTSM (a type of Recurrent Neural Network) to build a deep learning model that can generate captions for an image.
unnatibshah/Powered-by-Sun
Leveraging Machine Learning to Forecast the Throughput of Solar Power along with Cost and Size Calculation.
unnatibshah/Registration-Form-with-database-connectivity
Registration Form with DB connectivity
unnatibshah/CSCI585-Databases
CSCI 585 - Database Systems (Fall 2022) | Graduate Level Course taught by Prof. Sathyanaraya Raghavachary at USC | Credits - 4
unnatibshah/Customer_Segmentation_and_Behavioral_Analysis
Analysis of customer behavior and segmentation using SQL
unnatibshah/Decision-Trees-as-Interpretable-Models
Create a decision tree, plot it, convert the rules into IF-THEN format, and utilize cost-complexity pruning for minimal tree and interpretable rules.
unnatibshah/Embedding_Models_Comparison
A repository to compare various text embedding models
unnatibshah/Event-Search-iOS-App
Developed an iOS Mobile application, which allows users to search for event information, ticketing information, save events as favorites, and post on Social Media..
unnatibshah/Event-Search-Ticketmaster
Developed a web application that allows you to search for event information using the Ticketmaster API, and the results will be displayed in a card in tabular format. The application will also allow users to mark events as “Favorites” and see the list of all events marked as favorites. Also, users can share a post on Facebook and a tweet on Twitter
unnatibshah/Image-Classification-with-CNN
To create a Convolutional Neural Network (CNN) in Keras with a TensorFlow backend, and to train CNNs to solve Image Classification problems.
unnatibshah/KNN-on-Vertebral-Column-Data-Set
Classification using KNN on Vertebral Column Data Set
unnatibshah/Regression-on-Combined-Cycle-Power-Plant-Data-Set
The dataset contains data points collected from a Combined Cycle Power Plant over 6 years (2006-2011), when the power plant was set to work with 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 (EP)
unnatibshah/Sorting-Visualizer
unnatibshah/Time-Series-Classification-Part1
Time Series Classification Part 1 Feature Creation Extraction. In this problem, we will classify the activities of humans based on time series obtained by a Wireless Sensor Network.
unnatibshah/Time-Series-Classification-Part2
Time Series Classification Part 2 Binary and Multiclass Classification. An interesting task in machine learning is classification of time series. In this problem, we will classify the activities of humans based on time series obtained by a Wireless Sensor Network.
unnatibshah/unnatibshah