The Data Analysis Bureau Podcast is a space for us to share ideas, projects, collaborations and opinions in the fields of Data Science, Machine Learning and Artificial Intelligence.
Industrialising Machine Learning: Data-Centric Machine Learning & ML Pipelines
Business leaders rely on data and analytics to decide and accelerate business initiatives. It’s hard to make difficult decisions confidently when 65% of decisions made are more complex than they were two years ago, according to Gartner. Machine learning solutions can help your organisation uncover new insights and make more informed decisions by improving your ability to sift through alerts as well as identify threats and trends. In this panel, you will learn how to build pipelines and AI systems, why data-centric machine learning can be valuable, and more. Learn more about: - The need for data-centric machine learning that prioritises data quality and pipeline robustness - How to build pre-packed pipelines for specific industry use cases - How to build strong AI systems from modular, weak AI pipelines and components - Key technological and organisational challenges that impact the success of machine learning projects - And much more! Speakers: - Eric Topham, CEO & Co-Founder at The Data Analysis Bureau - Rajdeep Biswas, Director, Advanced Analytics & Machine Learning at Microsoft - Nik Spirin, Co-founder & CEO at Metapixel AI
1/13/2022 • 1 hour, 15 seconds
Machine Learning and NLP for E-Commerce product description personalisation
2021 marks the second year of The Innovation Sandbox portal since it was launched and will see several new and continued projects taking place with new students and new partnerships. The Innovation Sandbox is a collaborative initiative at the confluence of industry-academia, allowing both academic types of research on real-world datasets and the transfer of cutting-edge machine learning research into industry application
In this episode, we will hear our scientists discuss their new project on the application of machine learning and natural language processing (NLP) for a leading e-commerce platform. They will guide us through challenges, goals and future implications of the projects as well as their time scale and next steps.