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Yogesh Patil's Projects

multiple-and-logistic-regression-in-spss icon multiple-and-logistic-regression-in-spss

In this project regression model is used that pertains to a summary estimate to how strongly crude death rate is dependenton other factors such as current health expenditure, food safety, physicians density and legislation score and predict the crudedeath rate accordingly. Also, logistic regression model is used that pertains to a summary estimate in order to predict thetype of education on the bases of sex and age.

nyc-parking-violations-using-big-data-frameworks-on-gcp icon nyc-parking-violations-using-big-data-frameworks-on-gcp

In recent years due to the rapid urbanization, there has been an increase in the population and thus the vehicle use. This has lead to an increase in the parking violation. Analyzing the parking violation data can help us in understanding the trends in context to, which type of parking infraction is issued at which location and at what time. There are several parameters on which this study can be extended which are presented in this paper. With the help of different Big Data frameworks mainly Pig, Hive, Spark and MapReduce the projects aims to analyze the different parking violations and understand the trend, and visualize the same in order to answers all the questions as in the research objective.

research-project icon research-project

Solar Irradiation Components PredictionUsing Meteorological Measures in Odeillo

salesforce-project icon salesforce-project

This project aimed at providing an integrated platform to the international students in order to bring the key serviceslike PPSN, GNIB etc at the finger tips of the International Students and hence reducing the time required to get adjustedand settled in Ireland. In this project Salesforce was used in order to explore the Salesforce ecosystem. Also to understandas to how we can deploy complex ERP systems online quickly by reducing development costs

smartphones-data-warehouse icon smartphones-data-warehouse

A data warehouse and business intelligence project on SmartPhone market dataset to answer non-trivial BI queries.

wildfire-prediction icon wildfire-prediction

In this project an interesting demonstration of machine learning in the field of wildfire prediction was performed. Thiswas achieved using historical remote sensing and weather data. Machine learning models using these data resulted positivelyin predicting accurate wildfires.

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