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Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
Initially, I was unaware of how this would cater to my career needs. But when I stumbled through the reviews given on the website. I went through many of them and found them all positive. I would... Read More
I came to the platform with no experience and now I am knowledgeable in Machine Learning with Python. No easy thing I must say, the sessions are challenging and go to the depths. I looked at graduate... Read More
For all telecommunication providers, using the call details record (CDR), it is quite easy to measure the level and strength of interaction across areas of coverage. Such measurement enables the providers to make further decisions regarding sales, promotions and engineering details to improve the quality of service amongst other things.
In this spark graphx project, we will be doing an analysis of the level and strength of interactions between different areas in the city of Milan. Our dataset for this big data project include datasets from Dandelion Open big data website which contains aggregated anonymized call records based on the calls exchanged between Telecom Italia Mobile users.
In this big data project, we will look at how to mine and make sense of connections in a simple way by building a Spark GraphX Algorithm and a Network Crawler.
In this Neo4j project, you will do network analysis using a graph database to find patterns on how a social network affects business reviews and ratings.