Practical Automated Machine Learning on Azure: Using Azure Machine Learning to Quickly Build AI Solutions

Deepak Mukunthu is a product leader with 16+ years of experience. With his experience in big data, analytics, and AI, Deepak has played instrumental leadership roles in transforming organizations and teams become data driven and adopt machine learning. He brings a good mix of thought leadership, customer understanding and innovation to design and deliver compelling products that resonate well with customers. In his current role of Principal Program Manager on Automated ML in the Azure AI platform group at Microsoft, Deepak drives product strategy and roadmap for Automated ML with the goal of accelerating AI for data scientists and democratizing AI for other personas interested in machine learning. In addition to shaping the product direction, he also plays an instrumental role in helping customers adopt Automated ML for their business-critical scenarios. Prior to joining Microsoft, Deepak worked at Trilogy where he played multiple roles - Consultant, Business development, Program manager, Engineering manager – successfully leading distributed teams across the globe and managing technical integration of acquisitions.

Parashar Shah works for Microsoft as a Senior Program/Product Manager in Azure Machine Learning platform engineering team. He is also an Subject Matter Expert (SME) in Cloud, Machine Learning and Big Data.Prior to Microsoft, he worked for Alcatel-Lucent/Nokia Networks/Bell Labs where he led engagements with global telecom operators (across North America, Europe, Middle East and APAC) as a solution architect/product manager. Parashar has a MBA from Indian Institute of Management Bangalore & B.E. (E.C.) from Nirma Institute of Technology, Ahmedabad. He also co-founded a Carpool startup in India. His first book, 'Hands-On Machine Learning with Azure: Build powerful models with cognitive machine learning and artificial intelligence', was published in Nov 2018. He has filed 5 patents (in published state). His interests spans across Photography, Artificial Intelligence, Machine Learning, AutoML, Big Data and Internet of Things (IoT).

Wee Hyong Tok is part of the AzureCAT team at Microsoft. He has extensive leadership experience leading multi-disciplinary team of engineers and data scientists, working on cutting-edge AI capabilities that are infused into products and services. He is a tech visionary with a background in product management, machine learning/deep learning and working on complex engagements with customers. Over the years, he has demonstrated that his early thought-leadership white papers on tech trends have become reality, and deeply integrated into many products. His ability to strategize, and turn strategy to execution, and hunting for customer adoption has enabled many projects that he works on to be successful. He is continuously pushing the boundaries of products for machine learning and deep learning. His team works extensively with deep learning frameworks, ranging from TensorFlow, CNTK, Keras, and PyTorch. Wee Hyong has worn many hats in his career - developer, program/product manager, data scientist, researcher, and strategist, and his range of experience has given him unique super powers to lead and define the strategy for high-performing Data and AI innovation teams. Throughout his career, he has been a trusted advisor to the C-suite, from Fortune 500 companies to startups.