pavantyagi Goto Github PK

followers: 9.0 following: 34.0 repos: 328.0 gists: 0.0

Name: Pavan Tyagi

Type: User

Bio: I am into Conceptualizing and implementing Augmented Systems ,AI,Machine Learning,Deep Learning and Robotic Process Automation

Location: Chicago,USA

Pavan Tyagi's Projects

packer-builder-softlayer

A builder plugin for packer.io for a SoftLayer cloud

pact-haskell-client

Haskell client for blockchain language and playground pact https://github.com/kadena-io/pact

pennylane

PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations

pennywise

Cross-platform application to open any website or media in a floating window

personality-insights-nodejs

:bar_chart:Sample Nodejs Application for the IBM Watson Personality Insights Service

phonebot

Slackbot using IBM Watson and Twilio to make phone calls via slack commands

predicting-paid-amount-for-claims-data

Introduction The context is the 2016 public use NH medical claims files obtained from NH CHIS (Comprehensive Health Care Information System). The dataset contains Commercial Insurance claims, and a small fraction of Medicaid and Medicare payments for dually eligible people. The primary purpose of this assignment is to test machine learning (ML) skills in a real case analysis setting. You are expected to clean and process data and then apply various ML techniques like Linear and no linear models like regularized regression, MARS, and Partitioning methods. You are expected to use at least two of R, Python and JMP software. Data details: Medical claims file for 2016 contains ~17 millions rows and ~60 columns of data, containing ~6.5 million individual medical claims. These claims are all commercial claims that were filed by healthcare providers in 2016 in the state of NH. These claims were ~88% for residents of NH and the remaining for out of state visitors who sought care in NH. Each claim consists of one or more line items, each indicating a procedure done during the doctor’s visit. Two columns indicating Billed amount and the Paid amount for the care provided, are of primary interest. The main objective is to predict “Paid amount per procedure” by mapping a plethora of features available in the dataset. It is also an expectation that you would create new features using the existing ones or external data sources. Objectives: Step 1: Take a random sample of 1 million unique claims, such that all line items related to each claim are included in the sample. This will result in a little less than 3 million rows of data. Step 2: Clean up the data, understand the distributions, and create new features if necessary. Step 3: Run predictive models using validation method of your choice. Step 4: Write a descriptive report (less than 10 pages) describing the process and your findings.

project-based-learning

Curated list of project-based tutorials

projects---adobeexperiencemanager

AEM sample bundle, content, apps

prometheus-redistimeseries-adapter

Prometheus remote storage adapter for RedisTimeSeries

protobuf

Protocol Buffers - Google's data interchange format

python

All Algorithms implemented in Python

python-machine-learning-book

The "Python Machine Learning (1st edition)" book code repository and info resource

python-patterns

A collection of design patterns/idioms in Python

python-sdk

:snake: Client library to use the IBM Watson services in Python and available in pip as watson-developer-cloud

pythonrobotics

Python sample codes for robotics algorithms.

qlearning

A simple game using Q-Learning artificial intelligence.

qminer

Analytic platform for real-time large-scale streams containing structured and unstructured data.

quickstart-eks-grafana

AWS Quick Start Team

quotientcube

MySQL UDF for creating a quotient cube.

rapidminer-studio

Easy-to-use visual environment for predictive analytics. No programming required. RapidMiner is easily the most powerful and intuitive graphical user interface for the design of analysis processes. Forget sifting through code! You can also choose to run in batch mode. Whatever you prefer, RapidMiner has it all.

rapping-neural-network

Rap song writing recurrent neural network trained on Kanye West's entire discography

react-components

React-based UI components used in Watson demos. Builds on top of our SASS UI Components library.

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