abhimanyu3-zz
Graduate student at Northeastern university having 2.5 yrs. of experience includes Data analysis, Reporting, Cluster analysis and Requirement Gathering.
Unity TechnologiesBoston, United States
Pinned Repositories
Customer-loan-prediction
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.
RedditBot_for_slack
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.
Spam-Detection-filter-using-NLP
Developed a spam detection filter with the help of NLTK library to segregate the difference between a ham and a spam text message.
twitterbot_for_slack
setting up a twitter bot to monitor multiple twitter account in real time and get real time notification in slack
adtk
A Python toolkit for rule-based/unsupervised anomaly detection in time series
amazon-emr-management-guide
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
Anomaly detection algorithm implementation in Python
Customer-churn-Management-in-R
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.
Data-Science
Elasticsearch-and-python
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.
abhimanyu3-zz's Repositories
abhimanyu3-zz/adtk
A Python toolkit for rule-based/unsupervised anomaly detection in time series
abhimanyu3-zz/amazon-emr-management-guide
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.
abhimanyu3-zz/RedditBot_for_slack
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.
abhimanyu3-zz/twitterbot_for_slack
setting up a twitter bot to monitor multiple twitter account in real time and get real time notification in slack
abhimanyu3-zz/Elasticsearch-and-python
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.
abhimanyu3-zz/Spam-Detection-filter-using-NLP
Developed a spam detection filter with the help of NLTK library to segregate the difference between a ham and a spam text message.
abhimanyu3-zz/Linear_Regression
Liner regression on different dataset
abhimanyu3-zz/Time-Series-and-Decision-tree
exploring the data avilable at LendingClub.com with Decision Tree and Random Forest
abhimanyu3-zz/Time-Series-Analysis
Time series analysis with inbuilt air passenger data in R
abhimanyu3-zz/Customer-loan-prediction
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.
abhimanyu3-zz/Principle-Component-Analysis
I have taken data set from an ongoing hackathon and implemented it with the help of some reference.
abhimanyu3-zz/Customer-churn-Management-in-R
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.
abhimanyu3-zz/Anomaly-Detection
Anomaly detection algorithm implementation in Python
abhimanyu3-zz/Data-Science
abhimanyu3-zz/pydata2015seattle
Tutorial materials for PyData 2015 Seattle.