Day165 - MLOps Review: Feature Engineering (2)
Designing Machine Learning Systems: Feature Engineering Techniques (2) (Positional Embeddings) & Engineering Good Features
Recent posts
Day164 - MLOps Review: Feature Engineering (1)
Designing Machine Learning Systems: Feature Engineering Techniques (1) (Handling Missing Values, Scaling, Normalization, Binning, Encoding Categorical Values...
Day163 - MLOps Review: Training Data (4)
Designing Machine Learning Systems: Data Augmentation (Simple Label-Preserving Transformations, Perturbation, and Data Synthesis)
Day162 - MLOps Review: Training Data (3)
Designing Machine Learning Systems: Class Imbalance (How to Deal with the problems: Evaluation Metrics, Over & Undersampling, Resampling and Algorithm-le...
Day161 - MLOps Review: Training Data (2)
Designing Machine Learning Systems: Labeling (Hand Labels, Natural Labels, & Addressing the Lack of Labels - Active Learning, etc.)
Day160 - MLOps Review: Training Data (1)
Designing Machine Learning Systems: Sampling (Nonprobability, Simple Random, Stratified, Weighted, Reservoir, and Importance Sampling)
Day159 - MLOps Review: Data Engineering Fundamentals (2)
Designing Machine Learning Systems: Modes of Dataflow & Batch / Real-Time Processing
Day158 - MLOps Review: Data Engineering Fundamentals (1)
Designing Machine Learning Systems: Data Formats (JSON, Parquet & Binary Format), Data Models (Relational & NoSQL), and Data Storage Engines (ETL)
Day157 - MLOps Review: Introduction to Machine Learning Systems Design (3)
Designing Machine Learning Systems: Framing ML Problems (2) (Types of ML Tasks & Objective Functions)
Day156 - MLOps Review: Introduction to Machine Learning Systems Design (2)
Designing Machine Learning Systems: Iterative Process & Framing ML Problems (1)