With the advances in machine learning (ML) and deep learning (DL) techniques, and the potency of cloud computing in offering services efficiently and cost-effectively, Machine Learning as a Service (MLaaS) cloud platforms have become popular. In addition, there is increasing adoption of third-party cloud services for outsourcing training of DL models, which requires substantial costly computational resources (e.g., high-performance graphics processing units (GPUs)). Such widespread usage of cloud-hosted ML/DL services opens a wide range of attack surfaces for adversaries to exploit the ML/DL system to achieve malicious goals. In this session, we will be learning around how to secure ML/DL services on the cloud.
About the speaker :
Antrixsh is one of the early data science practitioners in India. He actively contributes data science tutorials and creates courses for aspiring data science students. His research work involves computer vision learning on medical records.
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