About Me
Currently Research Engineer in Mercedes Benz research and development
• 4 years of experience in Analytics and Python.•Most of my work has been based on Python and R. • Hypothesis testing and Data Cleansing to give m...
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Others
Web Development
Data & Analytics
Programming Language
Database
Software Engineering
Mobile Apps
Operating System
Development Tools
Graphic Design
Positions
Portfolio Projects
Company
Solar Energy Production Forecast
Description
Solar Energy Production Forecast:
o Building Regression and Time Series methods.
o Forecastenergyproductionbybuilding ahybridmodel.[RNNandGBM]
o Forecast the amount of insurance claim received by insurance company.
Skills
Machine Learning PythonTools
GitCompany
Block ChainAnalysis
Description
- Data insights and Data preparation
- Classifying PO (use full form of PO) whether it will be in market or not.
- DelayPrediction-PredictingweatheraPOwillbelateorintime.Ifitisdelayed, predicting how many weeks it would be delayed.
Skills
Machine LearningTools
GithubCompany
Analytics Workbench
Description
- Workbench as a desktop widget: An interactive and essential tool for data analysts. This is a desktop version which includes regression (10 algorithms), classification (7 algorithms), clustering, time series (7 algorithms), dimensions reduction, association, few solutions like anomaly detection.
- Workbench as a web based: The desktop UI was migrated to web based along with other features like visualisation, big data, NLP, data base connection.
- Forecasting number of calls : forecasting the number of calls thats are made in a call centre for credit TL to support Mobiloans.
- Modularizing Forecasting tool: converting the R forecasting code into python and using oop concepts to modularise the forecasting tool.
- Forecasting the number of accidents: Forecasting the number of accidents happyening with the data by Vantage agora.
- Forecasting the number of claims: forecasting the number of insurance claims made for every month.
- Forecasting the amount of claims: forecasting the amount of claims per month using time series models/ regression models.
- Classification of customers : forecasting if a customer claims in the next year or not based on given data.
- Noise analysis: analysis of the noise present in the time series data.
Skills: Python, Machine Learning, Computer Vision, C++
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C++ Machine Learning PythonTools
Git