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| [ | |
| { | |
| "title": "From PDF to API: How I Built a Hybrid RAG Insights Engine for Laptop Specs", | |
| "description": "A deep dive into how I created a dynamic and static data-based RAG system for a business.", | |
| "url": "https://www.linkedin.com/pulse/from-pdf-api-how-i-built-hybrid-rag-insights-engine-laptop-abedheera-hwwoc", | |
| "type": "article" | |
| }, | |
| { | |
| "title": "How to Choose the Best Machine Learning Algorithm for Sentiment Analysis", | |
| "description": "A guide on how to choose the best machine learning algorithm for sentiment analysis.", | |
| "url": "https://www.linkedin.com/pulse/how-choose-best-machine-learning-algorithm-sentiment-abedheera-mvctc", | |
| "type": "article" | |
| }, | |
| { | |
| "title": "Parallel RAG with LangChain: Three Vector DBs, One Personality.", | |
| "description": "Lessons learned building an 'Uncle Iroh' mental healthcare assistant. Covers diverse knowledge sourcing, chunking strategies, and parallel retrievers.", | |
| "url": "https://www.linkedin.com/pulse/parallel-rag-langchain-three-vector-dbs-one-tharushika-abedheera-tognc", | |
| "type": "article" | |
| }, | |
| { | |
| "title": "A Gentle Introduction to LSTMs (Long Short-Term Memory Networks)", | |
| "description": "Explore what LSTMs are, why they were created, and how they help machines understand sequences.", | |
| "url": "https://www.linkedin.com/pulse/gentle-introduction-lstms-long-short-term-memory-tharushika-abedheera-irvzc", | |
| "type": "article" | |
| }, | |
| { | |
| "title": "How Does L1 (Lasso) and L2 (Ridge) Regularization Work?", | |
| "description": "Explore L1 (Lasso) and L2 (Ridge) regularization techniques to improve model performance by addressing overfitting.", | |
| "url": "https://www.linkedin.com/pulse/how-does-l1-lasso-l2-ridge-regularization-work-tharushika-abedheera-upyvc", | |
| "type": "article" | |
| }, | |
| { | |
| "title": "ROUGE Score: A Key Metric for Evaluating Text Summarisation Models", | |
| "description": "Introduction to how ROUGE scores provide valuable insights into how well a model has performed in generating summaries.", | |
| "url": "https://www.linkedin.com/pulse/rouge-score-key-metric-evaluating-text-summarisation-models-qirwc", | |
| "type": "article" | |
| }, | |
| { | |
| "title": "SQuAD Metrics: Evaluating Question-Answering Models Effectively", | |
| "description": "Introduction to the SQuAD metric, an essential tool for evaluating question-answering models in NLP.", | |
| "url": "https://www.linkedin.com/pulse/how-does-l1-lasso-l2-ridge-regularization-work-tharushika-abedheera-upyvc", | |
| "type": "article" | |
| } | |
| ] |