Machine Learning in 2020 with Zoiner Tejada
Machine Learning has been around for years, what does it look like today? Carl and Richard chat with Zoiner Tejada about how he approaches machine learning today, starting with a focus on data. The bulk of the work for using machine learning is focused on sources, quality and bias in data. Zoiner talks about using data lakes to organize data simply, and be able to filter it for processing quickly. Often, it makes sense to duplicate data for processing efficiency! The conversation then dives into the role of algorithms, training and testing, and what it means to be a data scientist.
Guests:
Zoiner Tejada
Zoiner Tejada has more than 20 years of experience in the software industry as a software architect, CTO, start-up CEO and venture investor, with particular expertise in cloud computing, big data, analytics, and machine learning. Beyond managing Solliance, Zoiner spends much of his time leading an expert team of data scientists and data engineers building sophisticated data pipelines for advanced analytics, capturing the best practices and learnings which the team delivers in trainings and hackathons to all sizes of customers. He was among the first to receive a Microsoft Azure MVP (“Most Valuable Professional”) designation and has since been awarded the MVP for eight consecutive years, including a dual MVP award for Azure and Data Platform and most recently for Artificial Intelligence (AI). Additionally, he is recognized by Microsoft as a Microsoft Regional Director. He received his Bachelor of Science in Computer Science from Stanford University in the height of the dot-com bubble.
Links:
- Bubbly https://leaverou.github.io/bubbly/
- Solliance https://solliance.net/
- Azure Data Lake https://azure.microsoft.com/solutions/data-lake/
- Azure Machine Learning https://azure.microsoft.com/services/machine-learning/
- Awesome GPT3 https://github.com/elyase/awesome-gpt3
- Introduction to Machine Learning https://www.udacity.com/course/intro-to-machine-learning--ud120