A computational study that ventures into the reduction of the standard error of a Monte Carlo simulation with the example of option pricing.
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Updated
Sep 22, 2023 - Python
A computational study that ventures into the reduction of the standard error of a Monte Carlo simulation with the example of option pricing.
Pyshifts: A Pymol Plugin for Chemical Shift-Based Analysis of Biomolecular Ensembles
Calculates the mass of an electron from the spectral lines of Hydrogen
This is the repo for NLP related tasks for Error and Design issue extraction from the corpus
Automate web-based tasks for data retrieval from specific dashboards with Python scripts developed at Infozillion Teletech BD Ltd. Optimize and analyze MNO and IPTSP files to generate comprehensive reports.
Nobunaga: Object Detection Analyzer
Tests the Black-Scholes model's performance on forecasting option call prices of a selected option chain dataset. Discusses factors such as volatility and time to expiration that affect the estimations of call option prices and how this occurs within the dynamics of the model.
Regression and Time Series course at IIT KGP
Cutting-edge Python scripts meticulously developed for Infozillion Teletech BD Ltd. to automate complex data retrieval and error analysis tasks.
Automate the aggregation and analysis of error code data from MNOs and IPTSPs with this Python script, developed at Infozillion Teletech BD Ltd. The script combines, processes, and summarizes data, providing a convenient "Grand Total" overview and generating an output CSV file for further analysis.
Process case studies on DEM uncertainty analysis at the Mont-Blanc massif and Northern Patagonian Icefield: Hugonnet et al. (2022).
Source code and the details of the results in the paper "Named entity recognition in Turkish: A comparative study with detailed error analysis".
Helping AI practitioners better understand their datasets and models in text classification. From ServiceNow.
Generate error bars and perform binning analysis using jackknife or bootstrap resampling. Calculate average and error in quantum Monte Carlo data (or other data) and on functions of averages (such as fluctuations, skew, and kurtosis).
OlliePy is a python package which can help data scientists in exploring their data and evaluating and analysing their machine learning experiments by utilising the power and structure of modern web applications. The data scientist only needs to provide the data and any required information and OlliePy will generate the rest.
Built an error prediction system using LSTM and integrated the model in Flask to make it a web application. Collected logs were trained using the model, and tested on the log data without error.
A tool for classifying mistakes in the output of parsers
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