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The Use Of Face Recognition Technology: Pros And Cons

In 2015, Snapchat started using face recognition technology in its app to identify users and their friends in photos. The app would scan a photo and compare it to images in its database to find matches. If it found a match, it would notify the user and suggest they add the person as a friend. […] ....

United States , Odes Ka Oblast , Bobby Murphy , Evan Spiegel , Reggie Brown , Bitmoji Party , Snapchat Face Recognition Technology , Facial Recognition , Play Store , Lens Feature , Oriented Gradients , Support Vector Machines , Active Shape Model ,

"A Cost-Sensitive Machine Learning Model With Multitask Learning for In" by Akbar Telikani, Nima Esmi Rudbardeh et al.

A problem with machine learning (ML) techniques for detecting intrusions in the Internet of Things (IoT) is that they are ineffective in the detection of low-frequency intrusions. In addition, as ML models are trained using specific attack categories, they cannot recognize unknown attacks. This article integrates strategies of cost-sensitive learning and multitask learning into a hybrid ML model to address these two challenges. The hybrid model consists of an autoencoder for feature extraction and a support vector machine (SVM) for detecting intrusions. In the cost-sensitive learning phase for the class imbalance problem, the hinge loss layer is enhanced to make a classifier strong against low-distributed intrusions. Moreover, to detect unknown attacks, we formulate the SVM as a multitask problem. Experiments on the UNSW-NB15 and BoT-IoT datasets demonstrate the superiority of our model in terms of recall, precision, and F1-score averagely 92.2%, 96.2%, and 94.3%, respectively, over ot ....

Eep Learning Dl , Nternet Of Things , Internet Of Things Iot , Intrusion Detection , Mathematical Models , Ultitask Learning , Upport Vector Machine Svm , Support Vector Machines , Task Analysis ,

A Deep Dive into Sentiment Analysis and Consumer Feedback

In the digital age, businesses have access to an unprecedented amount of data generated by consumers. One critical aspect of this data is consumer feedback, ....

Product Development , Customer Service Enhancement , Sentiment Analysis , Consumer Feedback , Text Data , Based Approaches , Learning Models , Support Vector Machines , Service Enhancement , Cultural Nuances , Data Protection , Natural Language Processing , Powered Chatbots ,

Azerbaijani young talent: From computer science to AI

Comparative Analysis of Machine Learning Algorithms for Sentiment Analysis of Text in Azerbaijani and English. ....

United States , Republic Of Azerbaijan , Mehdi Rasul , Hillary Clinton , Donald Trump , Cybermath Academy , Cisco Networking Academy , Artificial Intelligence , Machine Learning , Natural Language Processing , American Mathematics , Support Vector Machines , Logistic Regression , Count Vectorizer , Decision Tree , Random Forest , Naive Bayes ,

11 Essential AI and ML Python Libraries

11 Essential AI and ML Python Libraries
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Slovenia General , Neural Network Library , A Library , University Of Ljubljana , Montreal Institute For Learning Algorithms , Machine Learning , Artificial Intelligence , Google Brain , Support Vector Machines , Random Forest , Montreal Institute , Learning Algorithms , Python Based Reinforcement Learning , Library Driven Revolution ,