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Phishing Website Detection Using Machine Learning Algorithms

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A Machine-Learning Approach to Phishing Detection and Defense

Approach to Phishing Detetion and Defense have conducted research to demonstrate how a machine learning algorithm can be used as an effective;

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Hybrid Machine Intelligence for Medical Image Analysis

features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer;

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Hands-On Artificial Intelligence for Cybersecurity

defenses using AI. What you will learn Detect email threats such as spamming and phishing using AI Categorize APT, zero-days, and polymorphic;

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Ensemble Machine Learning Cookbook

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular;

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Machine Learning and Big Data

interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as;

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Genetic Algorithms, Fuzzy Systems & Website Classification

chain through fuzzy outranking techniques; fast web page classification without accessing the web page using machine learning techniques;

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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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Machine Learning for OpenCV 4

image processing systems using OpenCV 4 Key Features Gain insights into machine learning algorithms, and implement them using OpenCV 4 and;

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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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Machine Learning Using R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition;

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Malware Detection Techniques using Machine Learning Classifiers

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Hands-On Machine Learning with C++

, ensemble learning, and anomaly detection using modern C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib. Next;

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Rice Plant Diseases Detection Using IoT & Machine Learning

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Machine Learning and Visual Perception

, face recognition, deep learning, time series recognition, image classification, and object detection.;

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An intrusion detection system using machine learning algorithm

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Machine Learning with scikit-learn Quick Start Guide

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering;

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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

learning algorithms using practical examples. Whether it is an instance-based learning algorithm, Bayesian estimation, a deep neural network, a;

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40 Algorithms Every Programmer Should Know

detection using network analysis Work with machine learning algorithms to cluster similar tweets and process Twitter data in real time Predict the;

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

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts;

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Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us

supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image;

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Practical Machine Learning and Image Processing

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins;

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Practical Machine Learning and Image Processing

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins;

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Hands-On Machine Learning with ML.NET

Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity;

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Machine Learning Algorithms

differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and;

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Machine Learning Fundamentals

supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit;

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Machine Learning Applications for Accounting Disclosure and Fraud Detection

Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies;

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