kasthuriraajan

kasthuriraajan's Stars

• bradtraversy/design-resources-for-developers

  Curated list of design and UI resources from stock photos, web templates, CSS frameworks, UI libraries, tools and much more

  58.6k9799611.5k

• carbon-language/carbon-lang

  Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)

  Language:C++32.3k3856041.5k

• Ebazhanov/linkedin-skill-assessments-quizzes

  Full reference of LinkedIn answers 2024 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers

  28.4k36988413.4k

• iterative/dvc

  🦉 Data Versioning and ML Experiments

  Language:Python13.7k1384.7k1.2k

• careercup/CtCI-6th-Edition

  Cracking the Coding Interview 6th Ed. Solutions

  Language:Java11.3k606744.4k

• walkccc/CLRS

  📚 Solutions to Introduction to Algorithms Third Edition

  Language:Markdown4.7k612011.3k

• APIs-guru/openapi-directory

  🌐 Wikipedia for Web APIs. Directory of REST API definitions in OpenAPI 2.0/3.x format

  3.9k1131.2k579

• Azure/azure-sdk-for-java

  This repository is for active development of the Azure SDK for Java. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/java/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-java.

  Language:Java2.3k41710.9k2k

• microsoft/MLOps

  MLOps examples

  Language:Jupyter Notebook1.8k7120542

• actions/setup-java

  Set up your GitHub Actions workflow with a specific version of Java

  Language:TypeScript1.5k80333743

• apache/opennlp

  Apache OpenNLP

  Language:Java1.4k900449

• paiml/practical-mlops-book

  [Book-2021] Practical MLOps O'Reilly Book

  Language:Jupyter Notebook707193284

• ballerina-platform/openapi-connectors

  Generate Ballerina connector with OpenAPI definition

  Language:Ballerina12472040

• srijiths/MLOps-IRIS

  Create a fully automated, end-to-end IRIS Training and Deployment using Azure MLOps

  Language:Python5948202

• jhnwr/non-blocking-requests

  442213

• srivatsan88/ContinousModelDeploy

  This is code depository for my upcoming session. Will update details post the session

  Language:Jupyter Notebook392152

• elleobrien/automatic_testing

  Language:Python212028

• aaivu/aaivu-ride-hailing-simulation

  Ride Hailing Simulation - A data-driven approach to model a simulation environment

  Language:Jupyter Notebook11102

• aaivu/aaivu-dialogue-policy-optimization

  Dialogue policy optimization in low resource setting

  Language:OpenEdge ABL43

• cc-cobracode/loginapp-backend

  Language:Java3

• aaivu/aaivu-project-template

  This is the project template for any new projects

  21

• aaivu/aaivu-task-oriented-conversational-agent

  Building a task-oriented conversational agent for low resource setting using RL for dialogue policy optimization and ensembling for Natural Language Understanding

  Language:OpenEdge ABL2103

• aaivu/aaivu-tesseract-quality-api

  Tesseract Quality Checker API for checking quality of the image for tesseract API

  Language:Python20

• aaivu/aaivu-website

  Initial page of all the projects under Aaivu Organization.

  Language:JavaScript2100

• openmrs/openmrs-content-hiv

  An HIV content package for OpenMRS

  25003

• aaivu/aaivu-dd-strategies-sl-schools

  Data-Driven instruction strategies for Sri Lankan high schools

  Language:Python11

• aaivu/aaivu-documentations

  This repository contains all the documentation of Aaivu Org.

  10

• aaivu/aaivu-introduction

  Introduction to Aaivu Organization

  10

• aaivu/aaivu-machine-trans-eng-sin

  English to Sinhala Neural Machine Translation

  Language:Python12

• aaivu/aaivu-semantic-table-interpretation

  Semantic Table Interpretation is the use of external knowledge bases or ontologies to provide context to tabular data sources. Data usually loses its context when converted into tabular structures. Hence, mapping these data back into its original context is non trivial. Since table data is one of most widespread structures in use, the information loss is significant. In this project, we introduce a two novel algorithms, ReleX and STEM, to derive meaning full relationships between table columns and to identify table entities with context using web ontologies.

  120