Subtitled "The Art of Analyzing Hacked and Leaked Data", this hands-on guide blends real-world techniques for researching large datasets with lessons on coding, data authentication, and digital security. Micah Lee spices all of this up with stories from the front lines of investigative journalism, and looks into exposed datasets from a wide array of sources: the FBI, the DHS, police intelligence agencies, extremist groups like the Oath Keepers, and even a Russian ransomware gang.
<ASIN:1718503121 >
Author: Micah Lee Publisher: No Starch Press Date: January 2024 Pages: 544 ISBN: 978-1718503120 Print: 1718503121 Kindle: B0B9W11YNX Audience: General Level: Introductory/Intermediate Category: Security
- Master encrypted messaging to safely communicate with whistleblowers.
- Secure datasets over encrypted channels using Signal, Tor Browser, OnionShare, and SecureDrop.
- Harvest data from the BlueLeaks collection of internal memos, financial records, and more from over 200 state, local, and federal agencies.
- Probe leaked email archives about offshore detention centers and the Heritage Foundation.
- Analyze metadata from videos of the January 6 attack on the US Capitol, sourced from the Parler social network.
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Grokking Machine Learning
Author: Luis G. Serrano Publisher: Manning Date: December 2021 Pages: 512 ISBN: 978-1617295911 Print: 1617295914 Kindle: B09LK7KBSL Audience: Python developers interested in machine learning Rating: 5 Reviewer: Mike James Another book on machine learning - surely we have enough by now?
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Machine Learning with PyTorch and Scikit-Learn
Author: Sebastian Raschka, Yuxi (Hayden) Liu & Vahid Mirjalili Publisher: Packt Date: February 2022 Pages: 770 ISBN: 978-1801819312 Print: 1801819319 Kindle: B09NW48MR1 Audience: Python developers interested in machine learning Rating: 5 Reviewer: Mike James This is a very big book of machine le [ ... ]
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