Pinned Repositories
ayee.github.io
Car-Price-Prediction-System
Technologies: Nutch 1.6, MapReduce in Java, Mahout. For selling a used car, its price can be predicted by giving some attributes. e.g. Car Model, total miles, engine type. Trained data will be provided to our system to predict the price for new data. Used Nutch to crawl car data from 52 states which is on craigslist.org. Over 0.3 million records were fetched. The content was then pruned using two MapReduce Jobs. The first MapReduce cleaned the data removing unwanted unicode symbols and incomplete data (information without car model or total miles or engine or price). The Second MapReduce extracted the required attributes and emitted in tsv format. This tsv was then provided to a Naïve Based Classifier in Mahout. A classification model was built from the training data. This models predicts the price when attributes like car model model, miles, engine was provided.
coursera_deeplearning_ai
Notes and homework of deeplearning.ai course by Andrew Ng on coursera
Crunchbase4J
Simple Java library for Crunchbase API
crunchbaseR
Use R and Neo4J to analyze startup and enterpreneur data from Crunchbase API
google-maps-services-python
Python client library for Google Maps API Web Services
h2o-sparkling
H2O and Spark interoperability
radiant
Business analytics using R and Shiny
ayee's Repositories
ayee/coursera_deeplearning_ai
Notes and homework of deeplearning.ai course by Andrew Ng on coursera
ayee/radiant
Business analytics using R and Shiny
ayee/ayee.github.io
ayee/Car-Price-Prediction-System
Technologies: Nutch 1.6, MapReduce in Java, Mahout. For selling a used car, its price can be predicted by giving some attributes. e.g. Car Model, total miles, engine type. Trained data will be provided to our system to predict the price for new data. Used Nutch to crawl car data from 52 states which is on craigslist.org. Over 0.3 million records were fetched. The content was then pruned using two MapReduce Jobs. The first MapReduce cleaned the data removing unwanted unicode symbols and incomplete data (information without car model or total miles or engine or price). The Second MapReduce extracted the required attributes and emitted in tsv format. This tsv was then provided to a Naïve Based Classifier in Mahout. A classification model was built from the training data. This models predicts the price when attributes like car model model, miles, engine was provided.
ayee/Crunchbase4J
Simple Java library for Crunchbase API
ayee/crunchbaseR
Use R and Neo4J to analyze startup and enterpreneur data from Crunchbase API
ayee/google-maps-services-python
Python client library for Google Maps API Web Services
ayee/h2o-sparkling
H2O and Spark interoperability
ayee/idverify
ayee/java-rest-binding
Java Bindings for the Neo4J Server REST API, providing an implementation of GraphDatabaseService
ayee/kafka-docker
ayee/MMCamScanner
Simulation of CamScanner app With Custom Camera and Crop Rect Validation
ayee/projects
ayee/python-nvd3
Python Wrapper for NVD3 - It's time for beautiful charts
ayee/python-tesseract
Automatically exported from code.google.com/p/python-tesseract
ayee/rutils
ayee/sifarish
Collection of recommendation engine implementation on Hadoop
ayee/tenable-search