Welcome to the repository for my conference paper on stock market analysis and predictive models. In this paper, I explore various models to analyze and predict stock market trends. I have employed a combination of traditional time series models and modern machine learning techniques to provide insights into stock price movements.
Deep Learning project October 2023
A Machine Learning based predictor to predict the language tag for a question posted on Stackoverflow. It is a Single label classification.
Sentiment Analysis of Tweets using Neural Networks with Pytorch
Automation of tests using selenium 4 , core java, testNG, Maven
My Hybrid Model (Deep Learning and Machine Learning) Projects
Meetei Mayek Character Recognition: Hybrid CNN+LSTM model for Meetei Mayek script recognition.
Time series regression modeling on a dataset of supermarket sales across years, with the Darts library in Python.
Ilokano-Tagalog Machine Language Translator
Predictive Modeling of Neurological State with Multidimensional Time Series Data in Parkinson Disease Patients
Three basic models of Recommender systems
My data science workshops made for Data Science at Georgia tech members
Methodology and code to use social data for forecasting shortage of essential commodities (gasoline/PPE/toilet paper) during disasters like hurricanes and pandemics
An end-to-end Hybrid Learning Model built using CNN+LSTM layers to detect covid-19 from Chest X-ray images. Comparative study has been performed along with modified CNN architectures of transfer learning models : Xception, MobileNet and VGG19. An end-trend web based application was developed using flask framework and was hosted using Heroku.
Detection of brain cancer is a tedious and very crucial job. Usage of image based clustering can provide a efficient and unsupervised method of brain cancer detection. Due to the nature of image data, direct clustering is highly impossible and inefficient. To overcome the above limitation, hybrid learning methods are adopted. Efficient utilisati…
A graphical simulator for the two-dimensional hybrid model of programmable matter.
A Semantic-aware Code Snippet Recommender
A project intended to bring context to embodied computational agents. Layered brains from hybrid models. Contextual Neurodevelopmental Dynamics & GSoC 2020 assoc content.
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