Machine Learning Security Principles

Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes

Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes by John Paul Mueller, Rod Stephens
English | December 30, 2022 | ISBN: 1804618853 | 450 pages | PDF, EPUB | 24 Mb
Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes (repost)

Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes
English | 2022 | ISBN: 9781804618851 | 450 Pages | PDF EPUB (True) | 22 MB
Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes

Machine Learning Security Principles
by John Paul Mueller

English | 2022 | ISBN: ‎ 1804618853 | 451 pages | True/Retail PDF EPUB | 24.23 MB
Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes

Machine Learning Security Principles: Keep data, networks, users, and applications safe from prying eyes
English | 2022 | ISBN: 1804618853 | 1136 pages | True EPUB, MOBI | 30.12 MB

Thwart hackers by preventing, detecting, and misdirecting access before they can plant malware, obtain credentials, engage in fraud, modify data, poison models, corrupt users, eavesdrop, and otherwise ruin your day
Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices

Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices (Cyber Ecosystem and Security) by Brij B. Gupta, Quan Z. Sheng
2019 | ISBN: 1138587303 | English | 364 pages | PDF | 19 MB

Blockchains for Network Security: Principles, technologies and applications  eBooks & eLearning

Posted by AvaxGenius at Dec. 17, 2020
Blockchains for Network Security: Principles, technologies and applications

Blockchains for Network Security: Principles, technologies and applications by Haojun Huang
English | PDF (True) | 2020 | 337 Pages | ISBN : 1785618733 | 9.01 MB

Blockchain technology is a powerful, cost-effective method for network security. Essentially, it is a decentralized ledger for storing all committed transactions in trustless environments by integrating several core technologies such as cryptographic hash, digital signature and distributed consensus mechanisms. Over the past few years, blockchain technology has been used in a variety of network interaction systems such as smart contracts, public services, Internet of Things (IoT), social networks, reputation systems and security and financial services.
Designing a Machine Learning Intrusion Detection System: Defend Your Network from Cybersecurity Threats

Designing a Machine Learning Intrusion Detection System: Defend Your Network from Cybersecurity Threats
.MP4, AVC, 1920x1080, 30 fps | English, AAC, 2 Ch | 52m | 181 MB
Instructor: Emmanuel Tsukerman
Amazon SageMaker Best Practices: Proven tips and tricks to build successful machine learning solutions on Amazon SageMaker

Amazon SageMaker Best Practices
by Sireesha Muppala, PhD, Randy DeFauw and Shelbee Eigenbrode

English | 2021 | ISBN: ‎ 1801070520 | 348 pages | True (PDF EPUB MOBI) | 76.79 MB

Build 20 Real World Data Science & Machine Learning Projects  eBooks & eLearning

Posted by lucky_aut at Aug. 9, 2021
Build 20 Real World Data Science & Machine Learning Projects

Build 20 Real World Data Science & Machine Learning Projects
Duration: 13h 4m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 7.21 GB
Genre: eLearning | Language: English

Learn To Build Machine Learning, Data Science, Deep Learning, NLP Projects With Python Course
Hands-on Scikit-Learn for Machine Learning Applications: Data Science Fundamentals with Python (Repost)

Hands-on Scikit-Learn for Machine Learning Applications: Data Science Fundamentals with Python by David Paper
English | True EPUB | 247 Pages | ISBN : 1484253728 | 2.5 MB

Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine.