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.

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/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.