OONNELLABinonnellab.hashnode.dev·Sep 23 · 8 min readWhat Makes Large Text Files Slow to OpenThe constraint to solve A large text file is slow to open when the application does too much work before showing the first useful screen. That work may include reading every byte, decoding the entire 00
YPYogeshwar Peelainexploitnotes.hashnode.dev·Jul 12 · 4 min readBroncoCTF : Spot the difference WriteupChallenge We're given two files, file1.txt and file2.txt, each containing what looks like a long, random blob of letters, digits, and symbols — one character per line. At a glance the two files look i00
BBuraqinburaqwrites.hashnode.dev·May 11 · 19 min readEveryday Text Problems and How to Fix ThemIntroduction: You Are Not Alone Let's be honest. Text is simple, right? You type letters, they appear on screen. Done. Except when it's not. You paste something from a website and suddenly there are w10
BBuraqinburaqwrites.hashnode.dev·May 10 · 9 min readStop Doing These 5 Text-Cleaning Tasks Manually (There's a Better Way)Hey there. Let me guess what you've been doing. You copy something from a website. Maybe a product description. Maybe an article you're quoting. Maybe some code from Stack Overflow. And then... the ni10
SSShivankur Sharmainshivankur018.hashnode.dev·Apr 30 · 4 min readInfosys Springboard: PaperIQOverview As part of the Infosys Springboard DSAI Virtual Internship, I worked on building PaperIQ, an end-to-end intelligent system designed to analyze research papers and convert them into structured00
FCFederico Calòinfedericocalo.hashnode.dev·Mar 20 · 1 min read10 - Monitoring NLP: Detecting Drift and Scheduling RetrainingComplete guide to Monitoring NLP: Detecting Drift and Scheduling Retraining: architecture, practical implementation and best practices for developers and technical teams. What you'll learn Types of Drift in NLP Models Structured Prediction Loggi...00
FCFederico Calòinfedericocalo.hashnode.dev·Mar 20 · 1 min read09 - Semantic Similarity: Measuring Text RelevanceComplete guide to Semantic Similarity: Measuring Text Relevance: architecture, practical implementation and best practices for developers and technical teams. What you'll learn Use SBERT instead of standard BERT for semantic similarity (Pearson 0.87...00
FCFederico Calòinfedericocalo.hashnode.dev·Mar 20 · 1 min read07 - HuggingFace Transformers: Models, Datasets, TrainingComplete guide to HuggingFace Transformers: Models, Datasets, Training: architecture, practical implementation and best practices for developers and technical teams. What you'll learn Use AutoClass to load any architecture with the same code The Pip...00
FCFederico Calòinfedericocalo.hashnode.dev·Mar 20 · 1 min read06 - Text Classification: Single and Multi-label ApproachesComplete guide to Text Classification: Single and Multi-label Approaches: architecture, practical implementation and best practices for developers and technical teams. What you'll learn Text Classification Taxonomy Multi-class Classification wit...00
FCFederico Calòinfedericocalo.hashnode.dev·Mar 20 · 1 min read05 - Named Entity Recognition: Extracting Information from TextComplete guide to Named Entity Recognition: Extracting Information from Text: architecture, practical implementation and best practices for developers and technical teams. What you'll learn 1.1 The BIO Format 1.2 NER Benchmarks and Datasets 2.1 Out-...00
