Sruthi RadhakrishnanTricky and innovative ways to create Knowlege Graphs“Ever wondered how to find or build Knowledge Graphs that power everything from recommendation engines to drug discovery?”4d ago4d ago
Sruthi RadhakrishnanKnowledge graphs in Action with a Q&A on Graph RAGKnowledge graphs are moving from Academia to Industry, this is validated by the Graph database providers using their services to analyse…May 3May 3
Sruthi RadhakrishnanAre you in need of an AI-assistant in Systems Engineering? — Welcome to LLMs that write QueriesSystems engineering is the ultimate balancing act of machines, software, and processes. Initially, engineers relied heavily on their own…Jul 31, 2023Jul 31, 2023
Sruthi RadhakrishnanNavigating AI’s Reality: The Role of KGs and LLMs in Fact-Checking“Ever wondered how we can catch our AGI’s ‘hallucinations’ and keep them grounded in reality?”Jul 18, 2023Jul 18, 2023
Sruthi RadhakrishnanUnlocking Change Impact Analysis: How a graph database and machine learning algorithms…In the ever-evolving world of technology, change impact analysis plays a crucial role in understanding the potential effects of alterations…May 19, 2023May 19, 2023
Sruthi RadhakrishnanFrom Network Analysis to Social Media Trends: top 4 graph dataset collections you need to KnowAre you trying to locate graph datasets for a future data analysis project? It might be difficult to know where to begin your search with…May 14, 2023May 14, 2023
Sruthi RadhakrishnanFrom Lab to Production: 3 Key insights on Machine learning operationsDo you know why only 13% of data science projects, or just one out of every 10, make it into production? — According to research [1], 87%…Apr 21, 2023Apr 21, 2023
Sruthi RadhakrishnanUnleashing the Potential: 2 Fascinating Graph-Based approaches across diverse domainsAccording to Gartner, graphs will be used in 80% of data and analytics breakthroughs by 2025 which is higher by 10% from previous years 📈.Apr 5, 2023Apr 5, 2023
Sruthi RadhakrishnanGot a partially labelled dataset? Four semi-supervised labelling algorithms to rescue!Semi-supervised graph-based algorithms are an efficient and accurate method of labelling data. To train the model, most supervised learning…Mar 27, 2023Mar 27, 2023
Sruthi RadhakrishnanWhy graph-databases are better for y(our) use case?We all know that “Data” plays a crucial role when understanding the use case. According to [2], 70% of the time before training an AI model…Feb 27, 2023Feb 27, 2023