Bridging the gap between theory and practical aspects of AI
About the speaker
Saurabh Ray is a visionary AI engineer, crafting innovative solutions in machine learning, blockchain, and more. His expertise spans Healthcare, Insurance, and Public Safety domains, positively impacting lives. A certified professional in Azure, AWS, and statistics, Saurabh enjoys mentoring and inspiring future talents. As a speaker and storyteller, he shares insights on research, data science, and tech advancements, inspiring audiences with passion and enthusiasm.
In this interactive session, Saurabh Ray takes us through his journey from a mechanical engineering background into the field of data science. He explains the key differences between Artificial Intelligence, Machine Learning, and Data Science to clarify common misconceptions. The discussion provides an introduction to much-talked-about AI models ChatGPT and BARD, followed by a deep dive into the practical aspects of developing and deploying AI solutions.
Saurabh outlines how machine learning models work under the hood and the technical knowledge required for applied AI projects. A key emphasis is understanding business problems and framing the right objectives before building ML models. The talk also covers which professions are at the highest risk of automation from advancing AI and the importance of honing soft skills like storytelling and visualization for maximum impact. Use cases across different industries are analyzed to demonstrate applied AI delivering value in real-world scenarios.
Watch the full video to learn how technical concepts are relatable and provide guidance on transitioning from theoretical foundations to developing practical AI applications focused on business outcomes.