Chio Clarence (36 results)

Condition: good. Book shows general signs of use and handling. May have light wear on the cover or edges and minimal writing or highlighting. Binding remains tight, and pages are clean and readable.

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Soft cover. Condition: Very Good. 1st Edition. Very good softcover with bright covers, no spine crease, light wear to wraps incl. corner bends from poor storage. Page are crisp & unmarked. See photos, if you have any questions please ask.

Condition: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Condition: As New. Unread book in perfect condition.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condition: New.

Paperback. Condition: new. Paperback. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, youll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis.Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike.Learn how machine learning has contributed to the success of modern spam filtersQuickly detect anomalies, including breaches, fraud, and impending system failureConduct malware analysis by extracting useful information from computer binariesUncover attackers within the network by finding patterns inside datasetsExamine how attackers exploit consumer-facing websites and app functionalityTranslate your machine learning algorithms from the lab to productionUnderstand the threat attackers pose to machine learning solutions About the Authors David Freeman is head of Anti-Abuse Relevance at LinkedIn, where he leads a team of machine learning engineers charged with detecting and preventing fraud and abuse across the LinkedIn site and ecosystem. He has a Ph.D. in mathematics from UC Berkeley and did postdoctoral research in cryptography and security at CWI and Stanford University. Clarence Chio is an engineer and entrepreneur who has given talks, workshops, and trainings on machine learning and security at DEF CON and other security/software engineering conferences/meetups across more than a dozen countries. He was previously a member of the security research team at Shape Security, a community speaker with Intel, and a security consultant for Oracle. Clarence advises a handful of startups on security data science, and is the founder and organizer of the Data Mining for Cyber Security meetup group, the largest gathering of security data scientists in the San Francisco Bay Area. He holds a B.S. and M.S. in Computer Science from Stanford University, specializing in data mining and artificial intelligence. In this practical guide, machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: new.

Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Paperback. Condition: New. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions.…

Paperback. Condition: New. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions.…

Condition: New.

Condition: New. 2018. 1st Edition. Paperback. . . . . .

Condition: New. pp. 300.

Condition: As New. Unread book in perfect condition.

Condition: New. In English.

Condition: New.

Condition: New. 2018. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Condition: New. pp. 300.

Condition: Neuf.

Condition: NEW.

Condition: New. pp. 300.

Paperback. Condition: new. Paperback. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, youll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis.Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike.Learn how machine learning has contributed to the success of modern spam filtersQuickly detect anomalies, including breaches, fraud, and impending system failureConduct malware analysis by extracting useful information from computer binariesUncover attackers within the network by finding patterns inside datasetsExamine how attackers exploit consumer-facing websites and app functionalityTranslate your machine learning algorithms from the lab to productionUnderstand the threat attackers pose to machine learning solutions About the Authors David Freeman is head of Anti-Abuse Relevance at LinkedIn, where he leads a team of machine learning engineers charged with detecting and preventing fraud and abuse across the LinkedIn site and ecosystem. He has a Ph.D. in mathematics from UC Berkeley and did postdoctoral research in cryptography and security at CWI and Stanford University. Clarence Chio is an engineer and entrepreneur who has given talks, workshops, and trainings on machine learning and security at DEF CON and other security/software engineering conferences/meetups across more than a dozen countries. He was previously a member of the security research team at Shape Security, a community speaker with Intel, and a security consultant for Oracle. Clarence advises a handful of startups on security data science, and is the founder and organizer of the Data Mining for Cyber Security meetup group, the largest gathering of security data scientists in the San Francisco Bay Area. He holds a B.S. and M.S. in Computer Science from Stanford University, specializing in data mining and artificial intelligence. In this practical guide, machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Condition: Brand New. 300 pages. 9.75x7.25x1.25 inches. In Stock.

Paperback. Condition: New. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions.…

Condition: New. In this practical guide, machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of sec.

Paperback. Condition: New. Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions.…