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Transformation

What is a transformation in ML?

A transformation is a function that is applied to some input data and produces processed data as output, such as a feature in a feature pipeline. In feature pipelines, you have model-independent transformations, while in training/inference pipelines you can find model-dependent transformations.

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AI Lakehouse
AI Pipeline
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AutoML
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Backfill features
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Backpressure for feature stores
Batch Inference Pipeline
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CI/CD for MLOps
Compound AI Systems
Context Window for LLMs
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DAG Processing Model
Data Compatibility
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Data Transformation
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Data Warehouse
Data-Centric ML
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ELT
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Idempotent Machine Learning Pipelines
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Natural Language Processing (NLP)
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Offline Store
On-Demand Features
On-Demand Transformation
Online Inference Pipeline
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KServe
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Python UDF
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Representation Learning
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RoPE Scaling
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SQL UDF in Python
Sample Packing
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Similarity Search
Skew
Splitting Training Data
Streaming Feature Pipeline
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Test Set
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Time travel (for features)
Train (Training) Set
Training Data
Training Pipeline
Training-Inference Skew
Two-Tower Embedding Model
Types of Machine Learning
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Upstream
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Validation Set
Vector Database
Versioning (of ML Artifacts)
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