Why Security Is Important in ML and How To Secure Your ML-based Solutions

Explore the critical importance of security in machine learning and learn practical strategies for safeguarding ML-based solutions in this 55-minute conference talk from MLCon. Delve into the unique vulnerabilities and risks associated with AI and ML technologies, particularly as enterprises undergo AI-powered digital transformations. Examine how the increased data requirements, complex algorithms, and cloud-based processing of ML systems create additional layers of security concerns. Focus on secure coding best practices and address security pitfalls specific to the Python programming language. Gain insights into both adversarial machine learning and core secure coding topics through hands-on labs and real-life examples. Discover techniques to enhance security engagement and significantly improve code hygiene in ML projects. Benefit from the expertise of speaker Rachid Kherrazi as he shares valuable knowledge to help mitigate cybersecurity risks in AI and ML implementations.