Day160 - MLOps Review: Training Data (1)
Designing Machine Learning Systems: Sampling (Nonprobability, Simple Random, Stratified, Weighted, Reservoir, and Importance Sampling)
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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)
Day155 - MLOps Review: Introduction to Machine Learning Systems Design (1)
Designing Machine Learning Systems: Business and ML Objectives & Requirements for ML Systems
A New Chapter:: Continuing onward to MLOps
Designing Machine Learning Systems (MLOPs) Review Begins!
Day154 - STAT Review: Unsupervised Learning (7)
Practical Statistics for Data Scientists: Scaling and Categorical Variables (Scaling the Variables, Dominant Variables, Categorical Data, and Gower’s Distanc...
Day153 - STAT Review: Unsupervised Learning (6)
Practical Statistics for Data Scientists: Model-Based Clustering (Multivariate Normal Distribution, Mixtures of Normals & Selecting the Number of Cluster...
Day152 - STAT Review: Unsupervised Learning (5)
Practical Statistics for Data Scientists: Hierarchical Clustering (A Simple Example, the Dendrogram, the Agglomerative Algorithm & Measures of Dissimilar...