Aparajita Das's Projects
This project aims to Analyze Box Office Data using different Visualization tools such as Seaborn, Plotly using Python.
Artificial Neural Network for Churn Modelling including Evaluating, Improving and Parameter Tuning
Convolution Neural Network to classify different Animals.
Recurrent Neural Network for Stock Prediction of Google.
Unsupervised, Self Organizing Map for Fraud Detection.
A python wrapper for Krähenbühls dense CRF for medical image volumes.
ML model to classify Interests, for Advertising Online Adds.
ML Model for Clustering Clients to increase Sales at Mall.
Python Music Player - using tkinter and pygame
Evaluation of Machine Learning Models with Yellowbrick
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, resulting in an ongoing pandemic. Long Short Term Memories(LSTMs) can solve numerous tasks not solvable by previous learning algorithms for recurrent neural networks (RNNs). LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition and anomaly detection in network traffic or IDS's (intrusion detection systems). LSTMs can also be efficiently applied for time-series predictions. In this project, its shows a four stacked LSTM network for early prediction new Coronavirus dissease infections in some of the mentioned affected countries (India, USA, Czech Republic and Russia) , which is based on real world data sets which are analyzed using various perspectives like day-wise number of confirmed cases, number of Cured cases, death cases. This attempt has been done to help the concerned authorities to get some early insights into the probable devastation likely to be effected by the deadly pandemic.
This Repo Consists of some of the Tasks for The Sparks Foundation-Machine Learning and Data Science Internship, containing Supervised and Unsupervised Machine Learning Techniques to solve A ML Problem in a Systematic Way.