Page History

...

A lot of possibilities for emerging data sets exist, as I found out while researching on the Internet :

1. Emerging data sets

...

1. made available by the European Union
   The European Union provides datasets on a number of subjects such as transportation, education, communication, population, economy and health.

2. Health-related data sets to track the health of people, to do genomic sequencing. MIRAGE( minimum information required for a glycomics(molecule) experiment) is another field for which public data is available.

3. World financial data such as the Balance of Payments, economic data made available by the International Monetary Fund.

4. Data

...

1. sets made available by the Stanford University on topics such as on-line community interaction.

2. Data sets made available by the

...

Environment data about the changing climate, CO₂ emissions made available by the World Bank.

...

Data set about the usage of digital content by people and usage of Internet made available by the World Bank.

...

1. World Bank on various subjects such as poverty, income, population , growth(in GDP), environment(CO₂ emissions), disease patterns across the world.

2. Amazon Web Services public datasets provides a huge resource of datasets such as the Common Crawl dataset which can be analyzed for almost any information on the web using tools such as the Warcbase project.

My main objective in the project would be to take up as many as possible of the above mentioned data sets and create notebooks for each of them using the existing support for the various interpreters. This would involve examining the datasets first to decide which of the interpreters would work best for which dataset and then to write out the notebook. The main interpreters that I propose to use in the project are Spark and Flink. Spark has a variety of powerful features that make it suitable for the analysis of datasets. Spark's MLLib Machine Learning libraries may be used to build regression models of the datasets and predict the values of the test data based on the training data set. Regression analysis may be achieved through inbuilt classes such as 'LinearRegressionWithSGD' available in MLLib. Other forms of analysis (such as classification and clustering) may also be performed using these libraries.

...

• A set of at least 4 notebooks for the above proposed data sets with at least 2 using Helium functionality.

• Documentation for the notebooks.

• Results of any tests and bug fixes that were encountered during the development phase.

I also propose to create a blog post to document my progress about the creation of notebooks all along the development cycle. The blog would contain detailed explanations about the various models implemented for the analysis of the datasets and it would welcome suggestions form anyone interested in commenting or advising anything about the notebooks being created or the approach taken to implement them.

Schedule :

April 22 – May 22 : This time would be utilized in interacting as much as possible with the community and the mentors and learning more about the project in general(the working of various components) and suggested methods of implementation in specific(such as prospects of inclusion of Helium in the project).

...