1 views collected around this technical thread.
This article explores the role of hyperparameters in large language models, explains each key hyperparameter, and guides readers through manual and automated tuning methods such as random search, grid search, and Bayesian optimization to achieve optimal model performance.
This article presents a comprehensive English summary of the deep learning specialization infographics originally shared by Andrew Ng, covering fundamentals, logistic regression, shallow and deep neural networks, regularization, optimization, hyperparameters, convolutional and recurrent networks, and practical advice for model building and evaluation.
This article explains the fundamentals of the Word2Vec SGNS model, details its hyper‑parameters and training tricks, and demonstrates how customized embeddings are built for rental‑listing and news‑article recommendation, covering data preparation, objective‑function redesign, evaluation, and deployment in both recall and ranking stages.