Building and Leading a Successful AI Practice for your Organization
Who is this presentation for?Rossella Blatt Vital, Director of Innovation - Machine Learning, Wonderlic
Machine learning is an exciting field with incredible untapped potential to create value and strengthen the organization’s competitive advantage. Creating and leading a successful ML strategy requires an elegant orchestration of many components: master the key ML concepts to make sound decisions that align with the company’s vision and mission, operationalize the ML workflow, prioritize highest value projects, know what to look for in ML talents (and how to develop it!), build and motivate high performing teams, nurture strategic partnerships (internal and external), etc. The goal of this tutorial is to empower leaders with the fundamental concepts, key insights and lessons learned to drive a successful Machine Learning Strategy.
The tutorial is divided in 2 parts: the first part offers a primer on machine learning, arming leaders with the understanding of the key ML concepts relevant to drive a high value ML roadmap. The second section focuses on strategic insights to build and lead a flourishing ML practice. In particular:
PART 1: A PRIMER ON MACHINE LEARNING
- What Machine Learning is and what it is not. What is the difference between Artificial Intelligence and Machine Learning? How does it relate to Data Science, Big Data, Programming, Traditional Statistical Methods? Brief history of AI, current trends and where it’s going.
- What problems can AI solve? ML approaches overview: the 5 tribes (symbolists, bayesians, connectionists, evolutionarists, analogizers) and their methods (respectively, decisions trees/random forests; bayesian inference and bayesian networks; artificial neural networks and deep learning; k-nn, support vector machines and recommender systems).
- Machine Learning & Statistics Pitfalls and how to prevent them
PART 2: HOW TO DEVELOP A SUCCESSFUL ML STRATEGY
- Operationalize AI (workflows and processes): the iterative process of building, training and deploying to production a machine learning product. How to manage an AI project.
- Talents and Team: How to create a high performing Machine Learning team. What skills are needed? how to recognize unicorns? When and how to effectively invest in development? Insights from I/O studies.
- The critical role of internal and external partnerships: executive buy in, partnership with business experts, the criticality of data strategy and partnership with other tech team. ML as key player in an open innovation ecosystem.
The tutorial aims at sharing some insights and lessons learned to empower other leaders to accelerate the success of their organization by harnessing the power of ML and driving a successful ML strategy.
Prerequisite knowledgeAnyone, regardless of background, could benefit from the topics presented; however some managerial and leadership experience will be beneficial
Materials or downloads needed in advance
What you'll learn
Rossella Blatt Vital
Rossella Blatt Vital, Director of Innovation – Machine Learning at Wonderlic, is a passionate and visionary thought leader in the field of artificial intelligence. She has 15+ years of experience driving Machine Learning strategies and leading ML teams, in both enterprise, SMB and startup environments. Her career began in the academic field, where she headed projects in machine learning that ranged from lung cancer diagnosis to a brain computer interface and crime forecasting. Rossella then transitioned to the corporate world, leading the AI and Data Science initiatives at Newedge and Société Générale before moving to Remitly to serve as the Director of Machine Learning.
Rossella is particularly motivated by empowering organizations to build a strong ML capability, generate value through ML and create high performing ML teams. A native of Italy, she holds an M.S. and B.S. in telecommunications engineering from Politecnico di Milano (which is when she discovered and fell in love with ML) and has pursued a Ph.D. (ABD) in Information Technology.
Rossella loves innovation and machine learning and how, when driven by the right principles and culture, they can contribute to make a difference and create a better tomorrow.
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