N-Gram
Noun · AI & Machine Learning
Definitions
N-Gram is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and research pipelines, where teams need predictable behavior under real workloads rather than toy examples. Practitioners pay attention to data fit, compute cost, and reliability, because those factors usually determine whether the approach improves quality, latency, reliability, or operating cost in production.
In plain English: N-Gram is an AI concept teams use to train models, guide predictions, or make model behavior more reliable and easier to control in practice.
Example: "We evaluated N-Gram in the new model pipeline because the baseline was plateauing; once it was wired into training and evaluation, quality improved enough to justify rolling it into the next release."
Related Terms
- Embedding Model
- Masked Language Model
- Multimodal Embedding
- Named Entity Recognition
- Natural Language Generation
- Natural Language Inference
- Natural Language Processing
- Natural Language Understanding
- Neural Machine Translation
- Positional Embedding
- Rope Embedding
- Rotary Position Embedding
- Sentence Embedding
- Sentence Transformer
- Sentiment Analysis
- Seq2Seq
- Sequence Modeling
- Sequence-to-Sequence
- Text Embedding
- Vector Embedding
- Word Embedding
- Word2Vec