TRThe rightmodeler teaminrightmodeler.hashnode.dev路4d ago 路 3 min readThe most expensive model in your agent might be doing the cheapest workAuthor: The rightmodeler team Imagine opening the graph for an agent you shipped six months ago. Every node uses the same frontier model. That does not mean the team was careless. It usually means the00
TRThe rightmodeler teaminrightmodeler.hashnode.dev路4d ago 路 3 min readWhy we built a model downgrade report before building a routerAuthor: The rightmodeler team The first version of our model cost tool does not route a single production request. At first, that can sound backwards. If the problem is expensive model calls, why not 00
RRishikantinrishiii2.hashnode.dev路Jun 28 路 7 min readThe ML Engineer's Playbook: Model Evaluation, Bias/Variance, and Strategic OptimizationUp to this point in our series, we have focused entirely on building and training models. We successfully coded Linear Regression, Logistic Regression, and Deep Neural Networks. But in the real world,00
HHemaNinhema-sdet.hashnode.dev路Apr 30 路 3 min readWhy One Metric Is Never Enough to Evaluate Generative AIAs I continue documenting my daily learning, today I focused on model evaluation for Generative AI, specifically understanding ROUGE, BLEU and BERT Score. These metrics are commonly used to evaluate t00
VUVishal Uttam Maneinvishal-uttam-mane-dataset.hashnode.dev路Apr 30 路 5 min readHandling Imbalanced DatasetsIn real-world machine learning applications, perfectly balanced datasets are more the exception than the rule. Whether in fraud detection, medical diagnosis, anomaly detection, or cybersecurity, the n00
SRStephane Royinflexai.hashnode.dev路Apr 27 路 5 min readHow to Benchmark Open-Source Models Before You CommitYou're choosing between Llama 4 Scout 17B, GPT-OSS 120B, and DeepSeek V3.2. The paper numbers look fine across all three. You pick the one that feels right and ship it. Three weeks later it fails on t00
RSRahul Sehrawatinai-zero-to-hero.hashnode.dev路Apr 12 路 10 min readOverfitting, Underfitting, and Why Your Model Lies to YouImagine a student who is, in one very specific sense, the best studier in her class. The teacher hands out a practice test before the real one. Our student takes it home and memorises it. Every question. Every answer. Every typo. If you ask her the t...00
RBRahul Bohrainrahul-bohra.hashnode.dev路Apr 6 路 6 min readThe ML Model's Tightrope Walk: Balancing Bias and Variance for Peak PerformanceThe ML Model's Tightrope Walk: Balancing Bias and Variance for Peak Performance Introduction: The Goldilocks Problem of Machine Learning Welcome, aspiring data scientists and ML enthusiasts! Ever wondered why some machine learning models perform bril...00
AAAbstract Algorithmsinabstractalgorithms.hashnode.dev路Mar 29 路 18 min readModel Evaluation Metrics: Precision, Recall, F1-Score, AUC-ROC ExplainedTLDR: 馃幆 Accuracy is a lie when classes are imbalanced. Real ML evaluation uses precision (how many positives are actually positive), recall (how many actual positives we caught), F1 (their balance), and AUC-ROC (performance across all thresholds). T...00
AAAbstract Algorithmsinabstractalgorithms.hashnode.dev路Mar 29 路 16 min readModel Evaluation Metrics: Precision, Recall, F1-Score, AUC-ROC ExplainedTLDR: 馃幆 Accuracy is a lie when classes are imbalanced. Real ML evaluation uses precision (how many positives are actually positive), recall (how many actual positives we caught), F1 (their balance), 00
