katerynad Goto Github PK

2016-us-president-election-primary-results-analysis

Correlation analysis between candidates and county facts based on 2016 US President Election Primary Results by county

analyzing-sequences

auto-insurance-risk-classification-and-claim-prediction

XGB model and feature importance to predict At Fault Auto Claims

aws-sage-maker-machine-learning-experiments-automation

Machine Learning experiments automation with the help of AWS Sage Maker using XGBoost Classification and Insurance Property data

aws_data_pipeline_samples

Few AWS Data Pipeline samples to demo export from MS SQL to a file in S3 bucket, load a DynamoDB table to Redshift, multiple dependencies in the flow

bartscraper

The application collects real time train departures from Bart API

boto3-demo

Examples of dynamic creation and use of VPC, EC2, Load Balancer, Auto Scaling group, Launch Configuration, Redshift cluster, S3, SQS, SNS

data-feeds

Advanced SQL

data-pipeline-samples

This repository hosts sample pipelines

eva.ru

What Russian women talk about - Natural Language Processing (NLP) research of Russian women eva.ru forum

insurance-data-pipelines

Pentaho Data Integration ETL and Matillion ELT

insurance-data-warehouse

Data Warehouse Modeling

katerynad

Config files for my GitHub profile.

katerynad.github.io

Personal site

mini-etl-tool

Mini ETL Tool is a Python module. It allows to run SQL and CLI commands in parallel or sequential mode, set up preconditions, dependencies and notifications

techcrunchpostsmulticlasspostsclassification

In this notebook I search the best classifier and its parameters for posts multi-class classifications based on authorship attributes

tweetsautorshipattributionmodelsevaluation

In this notebook I work on the question whether the author of a tweet (very short text) can be successfully identified. I try to choose the best classification method its parameters set and features

tweetslistener

Collects tweets and performs sentiment analysis based on emoticons and NLP (TextBlob)

water-peril-claims-research-with-xgboost-and-glm-models