Name: Abhimanyu
Type: User
Company: Unity Technologies
Bio: Graduate student at Northeastern university having 2.5 yrs. of experience includes Data analysis, Reporting, Cluster analysis and Requirement Gathering.
Location: Boston, United States
Blog: https://www.linkedin.com/in/abhimanyu3191/
Abhimanyu's Projects
A Python toolkit for rule-based/unsupervised anomaly detection in time series
The open source version of the Amazon EMR Management Guide. You can submit feedback & requests for changes by submitting issues in this repo or by making proposed changes & submitting a pull request.
Anomaly detection algorithm implementation in Python
Customer churn occurs when a customer stop doing business with services or company. In industries like telecommunication or insurance, churn is really useful as customer has option to choose from multiple service providers based on different factor and geographical area. I have used a telecom data set which i have downloaded from IBM sample dataset.
We are predicting whether any customer should get his\her loan approved or not on the basis of data we are having from the application process.
We often face service breakdowns and we can just see the overview of it in Grafana or Kibana in the form of time series but what if we want to dig deep and there is a need of root cause analysis. As our elastic cluster hold data for just the past two weeks so its very important that we should get the data of the breakdowns to analyze it and store it for future prospects. In this process I am going to describe certain ways to dump elastic cluster data into python in the form of data frame. Once we will get the raw data we can do any kind of analysis with it and can avoid same kind of interruption in future.
Liner regression on different dataset
I have taken data set from an ongoing hackathon and implemented it with the help of some reference.
Tutorial materials for PyData 2015 Seattle.
setting up a Reddit bot to monitor realtime subreddit headlines about user sentiments and getting that into slack channel and visualizing as a time series graph.
Developed a spam detection filter with the help of NLTK library to segregate the difference between a ham and a spam text message.
Time series analysis with inbuilt air passenger data in R
exploring the data avilable at LendingClub.com with Decision Tree and Random Forest
setting up a twitter bot to monitor multiple twitter account in real time and get real time notification in slack