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Beginning Anomaly Detection Using Python-Based Deep Learning

Beg-Int user level;...

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Beginning Anomaly Detection Using Python-Based Deep Learning

statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;

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Finding Ghosts in Your Data

Discover key information buried in the noise of data by learning a variety of anomaly detection techniques and using the Python programming;

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Applied Cloud Deep Semantic Recognition

and situational assessment using deep learning for anomalous detection, and how methods developed in one area can be applied in applications;

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Anomaly-Detection and Health-Analysis Techniques for Core Router Systems

Accurate Anomaly Detection Using Correlation-Based Time-Series Analysis; Presents the design of a changepoint-based anomaly detector; Includes;

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Anomaly-Detection and Health-Analysis Techniques for Core Router Systems

Accurate Anomaly Detection Using Correlation-Based Time-Series Analysis; Presents the design of a changepoint-based anomaly detector; Includes;

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Learn Computer Vision Using Opencv: With Deep Learning Cnns and Rnns

OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning;

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Finding Ghosts in Your Data

Discover key information buried in the noise of data by learning a variety of anomaly detection techniques and using the Python programming;

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Mastering OpenCV 4 with Python

application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book;

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HandsOn Unsupervised Learning Using Python

near impossible for humans to uncover. Author Ankur Patel shows you how to apply unsupervised learning using two simple, production-ready;

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Hands-On Image Processing with Python

enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn;

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Learning Data Mining with Python -

Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using;

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Network Anomaly Detection

detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and;

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Deep Learning with Applications Using Python

required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing;

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Deep Learning for Computer Vision

applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and;

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Python Image Processing Cookbook

solve real-world image processing problems Key Features Discover solutions to complex image processing tasks using Python tools such as scikit;

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Traffic Anomaly Detection

"typical day analysis". A new information-theory based technique for traffic anomaly detection (typical day analysis)

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Stevens:Deep Learning with PyTorc_p

Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection;

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Java Deep Learning Cookbook

from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural;

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Advanced Deep Learning with Python

networks using the Python ecosystem Key Features Get to grips with building faster and more robust deep learning architectures Investigate and;

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Anomaly Detection and Complex Event Processing Over IoT Data Streams

>Covers extraction (Anomaly Detection) Illustrates new, scalable and reliable processing techniques based on IoT stream technologies

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Applied Recommender Systems with Python

This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an;

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Applied Recommender Systems with Python

This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an;

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Deep Learning with Python

Cook The bestseller revised! Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using;

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Machine Learning and Data Science Blueprints for Finance From Building Trading Strategies to RoboAdvisors Using Python

learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based;

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Deep Learning with Structured Data

Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than;

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Python Machine Learning -

Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries;

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