Yassin Eljakani
Phd candidate in IoT/deep learning - FSA Ibn Zohr university
Agadir, Morocco
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Doctoral candidate in the field of improving connected object networks and deep learning at the Faculty of Sciences in Agadir. Possessing a Research Master's degree in Data Science and professional certifications from Google, Coursera. Led a team that won first prize at the Northern Africa Huawei Developer Competition. An active volunteer member of the association Science for All, working to improve digital capabilities in the Souss Massa region.
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Topics
Edge AI, Federated Learning, and IoT: Perfect Match?
In this session, we'll explore how Machine Learning moves to the edge with TinyML, enabling IoT devices to process data locally using frameworks like TensorFlow Lite. We'll present how Federated Learning allows these devices to collaboratively improve ML models without sharing raw data, enhancing privacy and security. Join us to discover how combining Edge AI, TinyML, TensorFlow, and Federated Learning can give the full potential of IoT, reducing latency, preserving privacy, and opening doors to innovative applications.
From Framework to Frontline: Risk Management using NIST CSF 2.0
In this talk, I will present the normalization of risk management through the NIST Cybersecurity Framework, focusing on its most recent iteration, CSF 2.0. This session will highlight the essential features of the NIST framework and explore its structured approach to identifying, protecting, detecting, responding to, and recovering from cybersecurity risks.
Large Language Models in Action with Vertex AI and LangChain
In this session, we will explore the integration of Vertex AI with the LangChain framework, showcasing their combined power in Generative AI applications. We'll introduce these cutting-edge technologies, explaining how LangChain streamlines the development of complex AI applications and enhances the capabilities of Large Language Models (LLMs), illustrating the seamless synergy between LangChain and Vertex AI. We will explore real-world applications, providing coding examples to demonstrate these technologies' integration process and transformative impact. The talk will culminate in a discussion on the future of AI development, emphasizing the endless possibilities that these advanced tools offer for developers and businesses looking to harness the power of Generative AI.
Large Language Models in Action with LangChain
In this session, we will explore the integration of LLMs with the LangChain framework, showcasing their combined power in Generative AI applications. We'll introduce these cutting-edge technologies, explaining how LangChain streamlines the development of AI applications. We will provide coding examples to demonstrate these technologies' integration processes. The talk will culminate in a discussion on the endless possibilities that these advanced tools offer for developers.
Yassin Eljakani
Phd candidate in IoT/deep learning - FSA Ibn Zohr university
Agadir, Morocco
Actions
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