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SKU/Artículo: AMZ-B0D5B991G5

Anomaly Detection: Through Machine Learning, Deep Learning and AutoML

Format:

Kindle

Detalles del producto

Disponibilidad:
Fuera de stock

Peso con empaque:
0.94 kg

Devolución:
No

Condición
Nuevo

Producto de:
Amazon

Viaja desde
USA

Sobre este producto

Welcome to the world of anomaly detection, an essential tool that can be leveraged across various industries to identify unusual patterns or data points that deviate from the norm. This capability is crucial for detecting critical issues such as fraud, system failures, and operational inefficiencies, making it valuable for any organization. Anomaly detection is an excellent starting point for any organization looking to embark on their AI journey. It consistently delivers valuable insights; once you identify an anomaly, you can investigate and analyze it to uncover areas for improvement. This process not only helps in enhancing operational efficiency but also in preempting potential issues before they escalate.In this book, we will cover both the basics as well as advanced topics:What constitutes an anomaly versus an outlierStatistical techniques to identify outliersIsolation Forest AlgorithmAdvanced deep learning approaches like Generative Adversarial Networks (GANs).Automated Machine Learning (AutoML) in tools like PowerBI can empower organizations to apply these complex models effortlessly, without needing deep technical expertise.Furthermore, we will highlight the importance of Explainable AI (XAI), which is pivotal in areas such as fraud detection where understanding the rationale behind flagged anomalies is as crucial as the detection itself.Last but not the least, we'll demystify what happens inside libraries by using simple datasets and manual calculations, helping you gain a deeper appreciation of the underlying processes.Join us as we explore how anomaly detection can serve as a core analytical process to drive significant improvements and safeguard operations in any organization, making it a key strategy in today’s data-driven landscape.

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