DDylan HoggSep 25 · 8 min readStatic embeddings: a practical guide to model2vecSentence-transformer embeddings work well, but they are slow on a CPU. For a few thousand texts, the speed doesn't matter. When you embed millions of texts, or need embeddings within a tight latency binfocruncher.hashnode.dev
MMunukutla Sri Shanmukha AdityaSep 4 · 4 min readWhy Accuracy Can Be Misleading in Failure Detection SystemsWhen evaluating a machine learning model, accuracy is usually one of the first metrics we look at. It is simple, intuitive, and easy to compare. But that simplicity can become a problem when the data 1Ashanmukha-aditya.hashnode.dev
TTharunAug 31 · 9 min readFrom Lines to Decisions: Why Regression Fails at ClassificationLast time, right at the end, I asked a question and then walked away from it. Will this order be late, or won't it? The final answer isn't a number on a continuous scale. It's a class: yes or no. Ever1tharunpandya.hashnode.dev
AAkashAug 5 · 12 min readBuilding Production-Ready ML Models: From Data to DeploymentI originally built these projects in college for learning purposes, and I’m sharing them now to pass along the experience and lessons I gained Machine learning projects often fail not because of poorakashbuilds.hashnode.dev
NNethmi AmashaAug 3 · 4 min readWhy Are Both Chi-Square Test and ANOVA (F-Test) Used for Classification?While studying Feature Selection in Machine Learning, I noticed something that confused me. My lecture notes said that both Chi-Square Test and ANOVA (F-Test) are suitable for classification problems.curiousdeveloperbyamasha.hashnode.dev
AAkshay YadavAug 1 · 9 min readPredictive Maintenance for Industrial MachinesProblem Statement A manufacturing plant wants to predict machine failure before it happens using live sensor readings (air/process temperature, rotational speed, torque, and tool wear), so that mainteprojectsoncs.hashnode.dev
AAman JainJul 16 · 10 min readBuilding a GPT Model from Scratch (Part 5): Fine-Tuning GPT-2 for Text ClassificationIn the previous article, we loaded OpenAI’s pretrained GPT-2 weights into the model we had built from scratch. Now, we will adapt that model for text classification—specifically, identifying whether acurious-pm.hashnode.dev
RRishikantJun 28 · 7 min readMastering Logistic Regression: Probability, Decision Boundaries, and Advanced RegularizationIn our previous post, we explored Linear Regression, learning how to predict continuous continuous values by fitting a hyperplane to data. But what happens when our goal isn't to predict a continuous rishiii2.hashnode.dev
KKevin HwangMay 29 · 13 min readBuilding Claude Auto Permission: Autonomy With LLM Classification(tl;dr: https://github.com/kevinhwang/claude-auto-permission) AI agents are becoming ever more capable as models, harnesses, and context engineering improve, and as every system becomes a surface fo6kevinhwang.dev
DDivyajot KaurApr 30 · 4 min readPart 4: Regression vs Classification: How Machines Predict & DecideIn the previous blog, we explored what Supervised Learning is and how models learn from data. Now, let's understand how Supervised Learning is used to solve real-world problems using two key approacheai-beginners-journey.hashnode.dev
