Turn AI From Experiment to Core Products
Turn AI From Experiment to Core Products


To turn AI into a core part of your business, you’ll need to build the flywheel to scale your training data-creation and model-building processes. Whether you are training a self-driving car, building a voice assistant or a customer service chatbot, the steps needed to effectively train a machine learning model at scale and deploy in production with confidence remains the same.

In this session we will showcase how to successfully launch AI product with quality training data:
· Identify key success factors when scoping a machine learning project
· Determine what kind of source data you need to make it successful
· Select annotation tools that best fit your project
· Monitor and audit quality of your training data
· Automate your training data pipeline


Meeta is a passionate, customer-obsessed product leader with a track record of strategizing, building and launching innovative products that solve real business problems.
As VP Product at Appen she is building a machine learning data annotation platform focused on Computer Vision, Autonomous Vehicles, Conversational AI and NLP. Prior to Appen, Meeta held several product leadership roles in Cisco Systems, Tokbox/Telefonica and Computer Associates with a focus on AI, Chatbots, Voice/Video and Data Analytics. She has an MBA Degree from UC Davis and engineering degree from National Institute of Technology, India.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

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