I have total 3 years of experience in Software Development in frontend and backend in various tech-stacks. Prior to that I have had Internships and Publications in the field of data-science and Machine Learning.
Project: Sunking Pay
Saas product with a Pay-as-you-Go system to facilitate the sales of solar products from Inventory Management to Leads, Orders & Loans, payments to replacement, reposession and SMS service to agents and customers.
Project: XPO Logistics Rail Optimizer
Facilitates end-to-end management from getting the quotation to pricing, order management, tendering & scheduling trips, shipping cargos to Invoices and final settlements.
Advisor – Neeraj Yadav, Mohit Bansal
Designed, developed, evaluated innovative predictive models and success metrics. Evaluation of classification algorithms, keyword extraction and Topic Modelling.
Advisor - Vishal Bansal
Identifying niche products for e-commerce websites. Performed data analysis (excel) lookup tables, extracting meaningful insights from data, using visualisation tools Matplotlib & seaborn.
Don't talk, and let your work do the talking!
During under-graduation I was keenly interested in the field of Data Science, Machine Learning & Neural Networks. I took courses, Internships and even wrote 3 research papers in varied fields which got puplished in reputed journals.
Time series tools and their usage in the biomedical field; specifically, in neuroscience, has not been previously quantified. This study evaluates the principles and applications of few classical time series tools, such as PCA, Neural Networks, ARMA/ARIMA Models, Markov Models, Hidden Markov Models, Fourier Analysis, Spectral Analysis.
This study quantifies the usage from two perspectives, one, information technology professionals’, other, researchers utilizing these tools for biomedical and neuroscience research.
Read More...Computer-aided diagnosis of retinopathy is a research hotspot in the field of medical image classification. Optical coherence tomography (OCT) is widely applied in the diagnosis of ocular diseases.
In this study we present the solution to classify the OCT images using simple baseline 3,5 and 7 Layer deep Convolutional Neural Networks (CNN). It also explores the effect of hyper-parameters such as dropout, image-size, batch normalization, epochs and their relationships with the accuracy, sensitivity and specificity of the models.
Read More...In this paper we did a comparative analysis on automated bug-clasification in the software Industry. We worked on characterization and prediction of different software issue types with respect to three parameters: distribution, mean time to repair, and top terms present in various issue types. We have compared several classic and ensemble machine learning classifiers with respect to accuracy and prediction time and provided detailed analysis on the same.
Read More...Hey! I am always open to new opportunities, get in touch.