Passionate about learning new technologies and latest innovations.Interested in Machine Learning and Data Science
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arunava_21
April 25, 2017 – May 26, 2017
My Personal Website Live at https://21arunava.github.io/arunava_21/
View ProjectDeloitte-E-Maverick-Analysis
April 24, 2017 – April 24, 2017
Submitted this Solutions as part of the Deloitte E-Maverick Competition
View ProjectDemonetization-Analysis
April 24, 2017 – April 24, 2017
Made an analysis of all the Classification Algorithms that are available by running them on the Demonetization Dataset.
View ProjectParallel-Programming
March 27, 2017 – March 27, 2017
Processing time of Two Serial Algorithms have been reduced by converting them to a Parallel Implementation using Open MP.
View ProjectGoogle-Interview-Solutions
January 30, 2017 – January 31, 2017
Google-Interview-Solutions — GitHub repository
View ProjectSelected-Spoj-Solutions
January 30, 2017 – April 24, 2017
Selected-Spoj-Solutions — GitHub repository
View ProjectContent-Based-Image-Retreival
January 18, 2017 – January 18, 2017
The aim of this project is to review the current state of the art in content-based image retrieval (CBIR), a technique for retrieving images on the basis of automatically-derived features such as color, texture and shape. My findings are primary based both on a review of the relevant literature and on exploring possible enhancements over the net.The need to find a desired image from a collection is shared by many professional groups, including journalists, design engineers and art historians. While the requirements of image users can vary considerably, it can be useful to characterize image queries into three levels of abstraction: primitive features such as color or shape, logical features such as the identity of objects shown and abstract attributes such as the significance of the scenes depicted. While CBIR systems currently operate effectively only at the lowest of these levels, most users demand higher levels of retrieval.
View ProjectCleaning-and-Transforming-Data
January 17, 2017 – January 17, 2017
I have used tools in Azure Machine Learning Studio along with R Jupyter Notebook to integrate, clean and transform data.
View ProjectData-Analysis-on-a-Data-Set-collected-by-Frances-Galton
January 17, 2017 – January 17, 2017
I have estimated the range of expected profitability for a lemonade stand.
View ProjectCultural Fit Analysis
The candidate shows an interest in data science and competitive programming, which suggests a drive for problem-solving. Project diversity is moderate, with a mix of data analysis, web development, and competitive programming. However, the lack of detailed project descriptions makes it difficult to fully assess alignment with a collaborative or product-focused culture.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, and no psychometric or English test scores are available.