rohannaik Goto Github PK

application-engineering-and-development

Java swing applications based on the best practices and software development concepts.

applied-machine-learning-in-finance

azuredatabricksbestpractices

Version 1 of Technical Best Practices of Azure Databricks based on real world Customer and Technical SME inputs

cookbook

The Data Engineering Cookbook

data-science--cheat-sheet

Cheat Sheets

data-warehouse-and-business-intelligence

Developed a data infrastructure for a retail superstore incorporating the advanced data architecture concepts. Defined scalable data models, reduced data redundancy by using junk dimensions and outriggers. Managed efficient data storage policies. Lastly, designed and developed interactive dashboards for sales managers using Tableau.

database-management-systems-and-database-design

SQL based data integration project involving various entities of a railways operations management. Used stored procedures, database triggers, temporary views and log tables to track the ticket booking, cancellation and railway employees management modules.

datasciencer

a curated list of R tutorials for Data Science, NLP and Machine Learning

datasleuthing

Exploratory Data Analysis using Python Libraries. Data Source: 2015 Census Data. Analyzed US census data based on various income buckets. Described the swekness and kurtosis of data. Identified the population distribution among men and women across races, occupation types and service types. Also, identified the outliers in data for income.

free-programming-books

:books: Freely available programming books

personalized-medicine-redefining-cancer-treatment

A lot has been said during the past several years about how precision medicine and, more concretely, how genetic testing is going to disrupt the way diseases like cancer are treated. But this is only partially happening due to the huge amount of manual work still required. Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). Currently, this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from textbased clinical literature.

sales-prediction

In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays and oil prices.