Adnan Masood - Automated Machine Learning: Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

Adnan Masood, PhD

BIRMINGHAMMUMBAI

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There are moments in your life that stick with you no matter the circumstances. For me, it was the moment that I first met Dr. Adnan Masood. It was not at a tech conference or at a work function. It was at a Sunday school event which both of our children attended. He introduced himself and asked me what I did. I usually just give a generic canned response as most folks I speak with outside of my field of work don't really get what I do. Instead, his eyes lit up when I told him that I work with data. He kept asking me deeper and deeper questions about some of the most obscure Machine Learning and Deep Learning Algorithms that even I had not heard in a long time. It is a nice realization when you find out that you are not alone in this world and that there are others who have the same passion as you.

It is this passion that I see Dr. Masood bringing to a quickly growing and often misunderstood field of Automated Machine Learning. As a Data Scientist working at Microsoft, I often hear from organizational leads that Automated Machine Learning will lead to the end of the need for data science expertise. This is truly not the case and Automated Machine Learning should not be treated as a "black-box" or a "One-size-fits-all" approach to feature engineering, data pre-processing, model training, and model selection. Rather, Automated Machine Learning can help cut down the time and cost affiliated with work that takes away from the overall beauty of Data Science, Machine Learning, and Artificial Intelligence.

The great news about the current publication you hold in your hand or read on your tablet is that you now have a nuanced understanding of the benefits of applying Automated Machine Learning with every current and future project in your organization. Additionally, you will get hands-on expertise leveraging AutoML with open-source packages as well as cloud solutions offered by Azure, Amazon Web Services, and Google Cloud Platform. Whether you are a seasoned data scientist, a budding data scientist, a data engineer, an ML engineer, a DevOps engineer, or a data analyst, you will find that AutoML can help get you to the next level in your Machine Learning journey.

Ahmed Sherif

Cloud Solution Architect, AI & Analytics Microsoft Corporation

Adnan Masood, PhD is an artificial intelligence and machine learning researcher, visiting scholar at Stanford AI Lab, software engineer, Microsoft MVP (Most Valuable Professional), and Microsoft's regional director for artificial intelligence. As chief architect of AI and machine learning at UST Global, he collaborates with Stanford AI Lab and MIT CSAIL, and leads a team of data scientists and engineers building artificial intelligence solutions to produce business value and insights that affect a range of businesses, products, and initiatives.

Jamshaid Sohail is passionate about data science, machine learning, computer vision, and natural language processing and has more than 2 years of experience in the industry. He has worked at a Silicon Valley-based start-up named FunnelBeam, the founders of which are from Stanford University, as a data scientist. Currently, he is working as a data scientist at Systems Limited. He has completed over 66 online courses from different platforms. He authored the book Data Wrangling with Python 3.X for Packt Publishing and has reviewed multiple books and courses. He is also developing a comprehensive course on data science at Educative and is in the process of writing books for multiple publishers.