A library to support distributed matrix computation for machine learning and data analysis
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Updated
Feb 17, 2018 - Scala
A library to support distributed matrix computation for machine learning and data analysis
Source code for the paper "k-Distance Approximation for Memory-Efficient RkNN Retrieval"
This repository consists of presentations about Advanced DBMS concepts.
C-Store : A column-oriented DBMS prototype (frozen)
Labs for Databases II
Developed an SQL engine that will run a subset of SQL queries using command-line interface
Indoor Spatial Queries: Modeling, Indexing, and Processing
Inverted index and Positional index for a set of collection to facilitate Boolean Model of IR. Inverted files and Positional files are the primary data structure to support the efficient determination of which documents contain specified terms and at which proximity.
Falcon: The world fastest data analytics engine
Simple search system that includes inverted index builder and boolean query processor for information retrieval.
Database Systems
Efficient caching for non-volatile memory-backed search indices. A thesis submitted for undergraduate honours for the degree Software Engineering.
This repo consists of all the assignments, projects, tasks of Information Retrieval course of FAST NUCES Spring 2023.
An efficient layer to perform query processing on top of Terrier
Tunable Query Optimizer for Web APIs and User Preferences
A search engine that ranks documents by relevance to a query using a weighting scheme, tokenization, stop word removal, and stemming
Implementation and artifacts for "User-Defined Operators: Efficiently Integrating Custom Algorithms into Modern Databases"
A DBMS project on Textile Store Management using StreamLit-Python for the frontend app
A lightweight database engine supporting CRUD, simple queries, and concurrency control with a CLI.
Leverages extensive power of multiple Machine Learning algorithms & LLM to provide in-depth answers to medical queries and predicts condition/diseases based on patient symptoms
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