Machine learning and AI use cases with Lalit Wadhwa
The Data Standard
Nowadays, many companies are inclined to carry out advanced machine learning solutions along with custom AI solutions to stand tall in the competitive market. Analytics is essential to improve the bottom lines so that you can increase the efficiency of your business. With machine learning and AI, it is effortless to get some comprehensive strategies for analytics that will help you to run your business successfully. With a view to that, you must include the machine learning strategies in the data structure. Lalit Wadhwa, is our guest in this episode. He is the EVP & Chief Technology Officer at Encora, a leader in the large and rapidly growing outsourced product development market. Lalit, brings a lot of insights about machine learning and Ai. His core experience as a hardware product engineer shines through this episode, as he talks about machine Learning and AI use cases This is a great episode, pointing out a few challenges that can be resolved with focusing on Data at all levels in the enterprise, let’s dive in.
Meet The Host
Data scientist at The Data Standard
Catherine Tao is a tech enthusiast looking for new methods for building connections with businesses around the world. Her extensive knowledge of data science allowed her to develop new solutions and implement them into existing ecosystems. She is currently working as a Data scientist and Exclusive Podcast Producer at The Data Standard.
Meet The Guest
EVP & Chief Technology Officer at Encora
I'm a transformative senior executive with a track record of deploying data science, analytics, AI solutions & digital services to scale customer engagement, and attaining $500M+ in revenue growth, $41M in margin growth, and $25M+ in productivity gains. I've cross-functional global leadership experience in data management, digital platforms, Blockchain, intelligent automation, supply chain management, product development, and managing business units. Expert in transforming global operations, introducing new revenue streams, and monetizing data to fuel innovation.