How Long to Read Beginning Anomaly Detection Using Python-Based Deep Learning

How Long Does it Take to Read Beginning Anomaly Detection Using Python-Based Deep Learning?

It takes the average reader 7 hours and 18 minutes to read Beginning Anomaly Detection Using Python-Based Deep Learning by Sridhar Alla

Assuming a reading speed of 250 words per minute. Learn more

Description

Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semi-supervised anomaly detection along with the basics of time series-based anomaly detection. By the end of the book you will have a thorough understanding of the basic task of anomaly detection as well as an assortment of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to Scikit-Learn and are able to create deep learning models in Keras and PyTorch. What You Will LearnUnderstand what anomaly detection is and why it is important in today's world Become familiar with statistical and traditional machine learning approaches to anomaly detection using Scikit-Learn Know the basics of deep learning in Python using Keras and PyTorch Be aware of basic data science concepts for measuring a model's performance: understand what AUC is, what precision and recall mean, and more Apply deep learning to semi-supervised and unsupervised anomaly detection Who This Book Is For Data scientists and machine learning engineers interested in learning the basics of deep learning applications in anomaly detection

How long is Beginning Anomaly Detection Using Python-Based Deep Learning?

Beginning Anomaly Detection Using Python-Based Deep Learning by Sridhar Alla is 427 pages long, and a total of 109,739 words.

This makes it 144% the length of the average book. It also has 134% more words than the average book.

How Long Does it Take to Read Beginning Anomaly Detection Using Python-Based Deep Learning Aloud?

The average oral reading speed is 183 words per minute. This means it takes 9 hours and 59 minutes to read Beginning Anomaly Detection Using Python-Based Deep Learning aloud.

What Reading Level is Beginning Anomaly Detection Using Python-Based Deep Learning?

Beginning Anomaly Detection Using Python-Based Deep Learning is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Beginning Anomaly Detection Using Python-Based Deep Learning?

Beginning Anomaly Detection Using Python-Based Deep Learning by Sridhar Alla is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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