Data Collection and Analysis in Hostile Environments

De: Horen Kuecuekyan

Narrado por: Virtual Voice

Know the data collection and contemporary tooling landscape, including available machine learning algorithms, Generative Adversary Networks (GANs), and Large Language Models (LLMs). The primary objective of any data collection is to extract and analyze the data for various purposes. This book emphasizes human behavior in hostile and conflict zones.

Over the past several decades, the practice of data collection has undergone a transformative evolution. It began with paper forms, in-person interviews, and observations, and progressed to sophisticated digital systems capable of gathering vast amounts of information almost in real-time. The advent of the digital revolution has fundamentally transformed the data collection landscape and democratized data collection. We delve into this transition, explaining the techniques employed over time.

Data analysis techniques are contingent upon the content and the goal of the analysis. The specific form of data collected in hostile and conflict zones necessitates additional preprocessing steps.

The author has over three decades of experience developing and implementing machine learning algorithms. He draws upon this expertise to provide comprehensive explanations of many approaches.