Data Collection for Machine Learning

📄️ Data Sources

Identifying and integrating various data sources: from relational databases and APIs to unstructured web data and IoT streams.

Comparing Relational and Non-Relational databases: choosing the right storage for your machine learning features and labels.

Mastering the techniques for harvesting data from the internet: REST APIs, GraphQL, and automated web scraping.

A deep dive into REST and GraphQL APIs: how to fetch, authenticate, and process external data for machine learning.

Understanding telemetry, event tracking, and edge-to-cloud data ingestion for mobile-first machine learning.

Mastering the challenges of high-velocity sensor data: MQTT protocols, edge processing, and time-series ingestion.