Devosmita Chatterjee's Projects
The project involves Hopfield models, supervised learning and unsupervised learning.
The project involves projective geometry, geometric transformations, modelling of cameras, feature extraction, stereo vision, recognition and deep learning, 3d-modelling, geometry of surfaces and their silhouettes, tracking, and visualisation.
The project shows how to create Python library or Python package.
A cooperative data cleaning standalone application.
Devosmita Chatterjee's Profile
The project involves the analysis and forecasting of time series on financial data.
The project involves the application of leverage statistics to identify and detect outliers.
The project involves the multivariate regression analysis of a dataset.
The project involves a practical optimization problem that is modelled and solved using some mathematical optimization methods and software.
The project involves the study of performance analysis of the missForest imputation method for imputing continuous and categorical variables simultaneously.
The project aims to find a model and investigate its capability to identify all possible kinds of complex traffic scenarios around autonomous vehicles.
The project shows how to run Python scripts in Power BI.
Safely render long_description/README files in Warehouse
The project involves various techniques for visualizing datasets.
The project is to design a method for distinguishing tablet components in micro-CT images using image segmentation.
The project involves sampling designs and summarizing data, maximum likelihood estimation of parameters, bootstrap, parametric and non-parametric inference, the analysis of variance, linear least squares, categorical data, elements of the decision theory and bayesian inference.
The project encompasses the statistical analysis of data using different clustering and feature selection techniques.
The project encompasses the statistical analysis of a high-dimensional data using different classification, feature selection, clustering and dimension reduction techniques.
The project involves the implementation of classical optimization methods such as gradient descent and penalty methods, evolutionary algorithms such as genetic algorithm, particle swarm optimization, and ant colony optimization in the solution of optimization problems.
The project involves the application of singular value decomposition (SVD) to impute missing values.
Forecasting with Gradient Boosted Time Series Decomposition
The project involves the estimation of energy consumption using time series analysis.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent