Billede af showet CyberSecurity Summary

CyberSecurity Summary

Podcast af CyberSecurity Summary

engelsk

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Læs mere CyberSecurity Summary

CyberSecurity Summary is your go-to podcast for concise and insightful summaries of the latest and most influential books in the field of cybersecurity.Each episode delves into the core concepts, key takeaways, and practical applications of these books, providing you with the knowledge you need to stay ahead in the ever-evolving world of cybersecurity.Whether you’re a seasoned professional or just starting out, CyberSecurity Summary offers valuable insights and discussions to enhance your understanding and keep you informed.You can listen and download our episodes for free on more than 10 different platforms:https://linktr.ee/cyber_security_summary

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1000 episoder

episode Github Essentials cover

Github Essentials

https://www.amazon.com/GitHub-Essentials-Achilleas-Pipinellis/dp/1783553715?&linkCode=ll2&tag=cvthunderx-20&linkId=5d8c27ffb442779efd5ef9abffc89b0b&language=en_US&ref_=as_li_ss_tlA comprehensive guide to mastering the GitHub platform. It details the fundamental processes of creating repositories, managing code versioning, and utilizing the issue tracker for project communication. The text highlights key collaborative features such as pull requests, wiki documentation, and the organization of teams and permissions. Additionally, it explores advanced tools like GitHub Pages for hosting websites and web analytics for monitoring repository traffic. By comparing terminal commands with the GitHub web interface, the source illustrates how to effectively transition from local development to a global collaborative workflow. You can listen and download our episodes for free on more than 10 different platforms: https://linktr.ee/cyber_security_summary [https://linktr.ee/cyber_security_summary] Get the Book now from Amazon: https://www.amazon.com/GitHub-Essentials-Achilleas-Pipinellis/dp/1783553715?&linkCode=ll2&tag=cvthunderx-20&linkId=5d8c27ffb442779efd5ef9abffc89b0b&language=en_US&ref_=as_li_ss_tl [https://www.amazon.com/GitHub-Essentials-Achilleas-Pipinellis/dp/1783553715?&linkCode=ll2&tag=cvthunderx-20&linkId=5d8c27ffb442779efd5ef9abffc89b0b&language=en_US&ref_=as_li_ss_tl] Discover our free courses in tech and cybersecurity, Start learning today: https://linktr.ee/cybercode_academy [https://linktr.ee/cybercode_academy]

I går - 21 min
episode Learning Robotics Using Python cover

Learning Robotics Using Python

A comprehensive guide for designing and building autonomous mobile robots. The material focuses on a specific case study of a service robot named ChefBot, detailing its progression from initial hardware requirements to mechanical 2D and 3D modeling. Key technologies discussed include Python, ROS, and OpenCV, which are utilized for simulation, navigation, and speech recognition. The sources further outline the architectural paradigms of robotics, explaining how sensors, controllers, and effectors work together to achieve autonomous movement. Practical tutorials cover everything from calculating motor torque to developing user interfaces and integrating artificial intelligence. Ultimately, these chapters provide a technical roadmap for engineering a functional interactive robot from the ground up. You can listen and download our episodes for free on more than 10 different platforms: https://linktr.ee/cyber_security_summary [https://linktr.ee/cyber_security_summary] Get the Book now from Amazon: https://www.amazon.com/Learning-Robotics-Using-Python-interactive/dp/1783287535?&linkCode=ll2&tag=cvthunderx-20&linkId=f855fbbf1436a75d4e99d0efe9df7948&language=en_US&ref_=as_li_ss_tl [https://www.amazon.com/Learning-Robotics-Using-Python-interactive/dp/1783287535?&linkCode=ll2&tag=cvthunderx-20&linkId=f855fbbf1436a75d4e99d0efe9df7948&language=en_US&ref_=as_li_ss_tl] Discover our free courses in tech and cybersecurity, Start learning today: https://linktr.ee/cybercode_academy [https://linktr.ee/cybercode_academy]

21. maj 2026 - 22 min
episode Learning Python Web Penetration Testing: Automate web penetration testing activities using Python cover

Learning Python Web Penetration Testing: Automate web penetration testing activities using Python

A comprehensive guide for automating security assessments using the Python programming language. Published by Packt Publishing, the material introduces the fundamental phases of professional penetration testing, including reconnaissance, mapping, and exploitation. Readers are taught to interact with web applications programmatically by leveraging powerful libraries like Requests and Scrapy to handle HTTP protocols. The source covers critical security vulnerabilities such as SQL injection and password cracking, while providing practical instructions for building custom tools like crawlers and proxies. Furthermore, the text outlines a hands-on testing environment using VirtualBox to ensure learners can safely practice these offensive security techniques. Overall, the book focuses on empowering developers and security professionals to automate manual tasks and adapt to unique cybersecurity challenges. You can listen and download our episodes for free on more than 10 different platforms: https://linktr.ee/cyber_security_summary [https://linktr.ee/cyber_security_summary] Get the Book now from Amazon: https://www.amazon.com/Learning-Python-Web-Penetration-Testing/dp/178953397X?&linkCode=ll2&tag=cvthunderx-20&linkId=c4c8c828b2e13a87d1e79178cbdcf600&language=en_US&ref_=as_li_ss_tl [https://www.amazon.com/Learning-Python-Web-Penetration-Testing/dp/178953397X?&linkCode=ll2&tag=cvthunderx-20&linkId=c4c8c828b2e13a87d1e79178cbdcf600&language=en_US&ref_=as_li_ss_tl] Discover our free courses in tech and cybersecurity, Start learning today: https://linktr.ee/cybercode_academy [https://linktr.ee/cybercode_academy]

20. maj 2026 - 21 min
episode Java Deep Learning Essentials cover

Java Deep Learning Essentials

A comprehensive introduction to building artificial intelligence using the Java programming language. The text traces the historical progression of AI through three major phases, highlighting how machine learning evolved to address complex pattern recognition tasks that traditional search algorithms could not solve. It emphasizes deep learning as a revolutionary breakthrough because it allows machines to automatically identify feature quantities from raw data, overcoming a significant limitation in standard machine learning known as feature engineering. Readers are introduced to core concepts such as supervised and unsupervised learning, along with specific algorithms like neural networks, Support Vector Machines, and Hidden Markov Models. The book aims to equip Java developers with the theoretical knowledge and practical skills to implement sophisticated algorithms like Convolutional Neural Networks and Deep Belief Nets. Ultimately, the source frames deep learning as an elegant, multi-layered approach that mimics the human brain to achieve unprecedented accuracy in image and voice recognition. You can listen and download our episodes for free on more than 10 different platforms: https://linktr.ee/cyber_security_summary [https://linktr.ee/cyber_security_summary] Get the Book now from Amazon: https://www.amazon.com/Java-Learning-Essentials-Yusuke-Sugomori/dp/1785282190?&linkCode=ll2&tag=cvthunderx-20&linkId=22e1ef35ac44ed5fa0085192f81b36e3&language=en_US&ref_=as_li_ss_tl [https://www.amazon.com/Java-Learning-Essentials-Yusuke-Sugomori/dp/1785282190?&linkCode=ll2&tag=cvthunderx-20&linkId=22e1ef35ac44ed5fa0085192f81b36e3&language=en_US&ref_=as_li_ss_tl] Discover our free courses in tech and cybersecurity, Start learning today: https://linktr.ee/cybercode_academy [https://linktr.ee/cybercode_academy]

19. maj 2026 - 21 min
episode Data Visualization and Knowledge Engineering: Spotting Data Points with Artificial Intelligence cover

Data Visualization and Knowledge Engineering: Spotting Data Points with Artificial Intelligence

Explores how artificial intelligence is used to identify and analyze complex data points. A significant portion of the material focuses on cross-project defect prediction, a method in software engineering that utilizes external datasets to anticipate errors in new software. The authors conduct experiments using machine learning classifiers and the SMOTE algorithm to demonstrate that predicting defects across different projects is as effective as traditional within-project methods. By addressing class imbalance issues through oversampling, the research highlights how specific object-oriented metrics can improve software quality and reliability. Additionally, the sources touch upon broader applications of these technologies, including recommendation systems for interactive entertainment and semantic segmentation for satellite imagery. You can listen and download our episodes for free on more than 10 different platforms: https://linktr.ee/cyber_security_summary [https://linktr.ee/cyber_security_summary] Get the Book now from Amazon: https://www.amazon.com/Data-Visualization-Knowledge-Engineering-Communications/dp/3030257967?&linkCode=ll2&tag=cvthunderx-20&linkId=614f4cb066b45f2d537535bc7e724fc0&language=en_US&ref_=as_li_ss_tl [https://www.amazon.com/Data-Visualization-Knowledge-Engineering-Communications/dp/3030257967?&linkCode=ll2&tag=cvthunderx-20&linkId=614f4cb066b45f2d537535bc7e724fc0&language=en_US&ref_=as_li_ss_tl] Discover our free courses in tech and cybersecurity, Start learning today: https://linktr.ee/cybercode_academy [https://linktr.ee/cybercode_academy]

18. maj 2026 - 21 min
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