Mon, 25 April 2022
In this episode, we speak with Abdullah Kurkcu, a Lead Traffic Modeler. Abdullah joins us to discuss his recent study on the effect of COVID-19 on bicycle usage in the US. He walks us through the data gathering process, data preprocessing, feature engineering, and model building. Abdullah also disclosed his results and key takeaways from the study. Listen to find out more.
Click here for additional show notes on our website. Thanks to our sponsor!
|
Fri, 22 April 2022
Today, we are joined by Jennifer Jacobs and Nadya Peek, who discuss their experience in teaching remote classes for a course that is largely hands-on. The discussion was focused on digital fabrication, why it is important, the prospect for the future, the challenges with remote lectures, and everything in between. Click here for additional show notes on our website! Thanks to our sponsor! Log, store, query, display, organize, and compare all your model metadata in a single place
Direct download: learning-digital-fabrication-remotely.mp3
Category:general -- posted at: 4:55am PDT |
Mon, 18 April 2022
Today, we are joined by Denae Ford, a Senior Researcher at Microsoft Research and an Affiliate Assistant Professor at the University of Washington. Denae discusses her work around remote work and its culminating impact on workers. She narrowed down her research to how COVID-19 has affected the working system of software engineers and the emerging challenges it brings.
Click here to access additional show notes on our website!
Thanks to our sponsor! Weights & Biases : The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management.
|
Mon, 11 April 2022
In this episode, we interview Jonas Landman, a Postdoc candidate at the University of Edinburg. Jonas discusses his study around quantum learning where he attempted to recreate the conventional k-means clustering algorithm and spectral clustering algorithm using quantum computing. |
Mon, 4 April 2022
K-means is widely used in real-life business problems. In this episode, Mujtaba Anwer, a researcher and Data Scientist walks us through some use cases of k-means. He also spoke extensively on how to prepare your data for clustering, find the best number of clusters to use, and turn the ‘abstract’ result into real business value. Listen to learn. Click here to access additional show notes on our website! Thanks to our sponsor!
ClearML is an open-source MLOps solution users love to customize, helping you easily Track, Orchestrate, and Automate ML workflows at scale. |