Data Skeptic

Today, we are joined by Alexander Thor, a Product Manager at Vizlib, makers of Astrato. Astrato is a data analytics and business intelligence tool built on the cloud and for the cloud. Alexander discusses the features and capabilities of Astrato for data professionals.

Direct download: modern-data-stacks.mp3
Category:general -- posted at: 7:00am PDT

Emojis are arguably one of the most effective ways to express emotions when texting. In today’s episode, Xuan Lu shares her research on the use of emojis by developers. She explains how the study of emojis can track the emotions of remote workers and predict future behavior. Listen to find out more!

Direct download: emoji-as-a-predictor.mp3
Category:general -- posted at: 7:25am PDT

On the show today, Fabian Braesemann, a research fellow at the University of Oxford, joins us to discuss his study analyzing the gig economy. He revealed the trends he discovered since remote work became mainstream, the factors causing spatial polarization and some downsides of the gig economy. Listen to learn what he found. 
Direct download: polarizing-trends-in-the-gig-economy.mp3
Category:general -- posted at: 6:39am PDT

On the show today, we interview Mouhamed Abdulla, a professor of Electrical Engineering at Sheridan Institute of Technology. Mouhamed joins us to discuss his study on remote teaching and learning in applied engineering. He discusses how he embraced the new approach after the pandemic, the challenges he faced and how he tackled them. Listen to find out more.

Click here for additional show notes on our website!

Thanks to our sponsor!
https://neptune.ai/

Log, store, query, display, organize, and compare all your model metadata in a single place

 

Direct download: remote-learning-in-applied-engineering.mp3
Category:general -- posted at: 5:29am PDT

It is difficult to estimate the effect on remote working across the board. Darja Šmite, who speaks with us today, is a professor of Software Engineering at the Blekinge Institute of Technology. In her recently published paper, she analyzed data on several companies' activities before and after remote working became prevalent. She discussed the results found, why they were and some subtle drawbacks of remote working. Check it out!

 

Click here for additional show notes on our website!

Direct download: remote-productivity.mp3
Category:general -- posted at: 5:45am PDT

We explore this complex question in two interviews today.  First, Kasey Wagoner describes 3 approaches to remote lab sessions and an analysis of which was the most instrumental to students.  Second, Tahiya Chowdhury shares insights about the specific features of video-conferencing platforms that are lacking in comparison to in-person learning.

Click here for 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.

 

Direct download: does-remote-learning-work.mp3
Category:general -- posted at: 6:00am PDT

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!
Astrato is a modern BI and analytics platform built for the Snowflake  Data Cloud. A next-generation live query data visualization and analytics solution, empowering everyone to make live data decisions.

 

 

Direct download: covid-19-impact-on-bicycle-usage.mp3
Category:general -- posted at: 5:46am PDT

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!
https://neptune.ai/

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

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.

 

Direct download: remote-software-development.mp3
Category:general -- posted at: 9:49am PDT

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. 

Click here to access additional show notes on our website!

Direct download: quantum-k-means.mp3
Category:general -- posted at: 6:00am PDT

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.
Direct download: k-means-in-practice.mp3
Category:general -- posted at: 6:00am PDT

Building a fair machine learning model has become a critical consideration in today’s world. In this episode, we speak with Anshuman Chabra, a Ph.D. candidate in Computer Networks. Chhabra joins us to discuss his research on building fair machine learning models and why it is important. Find out how he modeled the problem and the result found.

Click here to access additional show notes on our webiste!

Thanks to our sponsor!
https://astrato.io

Astrato is a modern BI and analytics platform built for the Snowflake Data Cloud. A next-generation live query data visualization and analytics solution, empowering everyone to make live data decisions.

Direct download: fair-hierarchical-clustering.mp3
Category:general -- posted at: 6:23am PDT

Many people know K-means clustering as a powerful clustering technique but not all listeners will be as familiar with spectral clustering. In today’s episode, Sibylle Hess from the Data Mining group at TU Eindhoven joins us to discuss her work around spectral clustering and how its result could potentially cause a massive shift from the conventional neural networks. Listen to learn about her findings.

Visit our website for additional show notes

Thanks to our sponsor, Weights & Biases

Direct download: matrix-factorization-for-k-means.mp3
Category:general -- posted at: 6:00am PDT

In this episode, we speak with Bernd Fritzke, a proficient financial expert and a Data Science researcher on his recent research - the breathing K-means algorithm. Bernd discussed the perks of the algorithms and what makes it stand out from other K-means variations. He extensively discussed the working principle of the algorithm and the subtle but impactful features that enables it produce top-notch results with low computational resources. Listen to learn about this algorithm.

Direct download: breathing-k-means.mp3
Category:general -- posted at: 6:00am PDT

In today’s episode, Jason, an Assistant Professor of Statistical Science at Duke University talks about his research on K power means. K power means is a newly-developed algorithm by Jason and his team, that aims to solve the problem of local minima in classical K-means, without demanding heavy computational resources. Listen to find out the outcome of Jason's study.

Click here to access additional show notes on our website!

Thanks to our Sponsors:
ClearML is an open-source MLOps solution users love to customize, helping you easily Track, Orchestrate, and Automate ML workflows at scale. https://clear.ml

Springboard
Springboard offers end-to-end online data career programs that encompass data science, data analytics, data engineering, and machine learning engineering.

Direct download: power-k-means.mp3
Category:general -- posted at: 6:00am PDT

In this episode, Kyle interviews Lucas Murtinho about the paper "Shallow decision treees for explainable k-means clustering" about the use of decision trees to help explain the clustering partitions. 

Thanks to our Sponsors:
ClearML is an open-source MLOps solution users love to customize, helping you easily Track, Orchestrate, and Automate ML workflows at scale.

Direct download: explainable-k-means.mp3
Category:general -- posted at: 6:17am PDT

Have you ever wondered how you can use clustering to extract meaningful insight from a time-series single-feature data? In today’s episode, Ehsan speaks about his recent research on actionable feature extraction using clustering techniques. Want to find out more? Listen to discover the methodologies he used for his research and the commensurate results.

Visit our website for extended show notes!

https://clear.ml/

ClearML is an open-source MLOps solution users love to customize, helping you easily Track, Orchestrate, and Automate ML workflows at scale.

Direct download: customer-clustering.mp3
Category:general -- posted at: 6:00am PDT

Linh Da joins us to explore how image segmentation can be done using k-means clustering.  Image segmentation involves dividing an image into a distinct set of segments.  One such approach is to do this purely on color, in which case, k-means clustering is a good option. 

Thanks to our Sponsors:
Visit Weights and Biases mention Data Skeptic when you request a demo!
&
Nomad Data 

In the image below, you can see the k-means clustering segmentation results for the same image with the values of 2, 4, 6, and 8 for k.

Lilac Crowned Amazon

 
Direct download: k-means-image-segmentation.mp3
Category:general -- posted at: 4:00pm PDT

In today’s episode, Gregory Glatzer explained his machine learning project that involved the prediction of elephant movement and settlement, in a bid to limit the activities of poachers. He used two machine learning algorithms, DBSCAN and K-Means clustering at different stages of the project. Listen to learn about why these two techniques were useful and what conclusions could be drawn.

Click here to see additional show notes on our website!

Thanks to our sponsor, Astrato

Direct download: tracking-elephant-clusters.mp3
Category:general -- posted at: 2:43pm PDT

Welcome to our new season, Data Skeptic: k-means clustering.  Each week will feature an interview or discussion related to this classic algorithm, it's use cases, and analysis.

This episode is an overview of the topic presented in several segments.

Direct download: k-means-clustering.mp3
Category:general -- posted at: 8:44am PDT

Frank Bell, Snowflake Data Superhero, and SnowPro, joins us today to talk about his book “Snowflake Essentials: Getting Started with Big Data in the Cloud.” 

Thanks to our Sponsors:

  • Find Better Data Faster with Nomad Data. Visit nomad-data.com
  • Visit Springboard and use promo code DATASKEPTIC to receive a $750 discount
Direct download: snowflake-essentials.mp3
Category:general -- posted at: 6:00am PDT

Zack Labe, a Post-Doctoral Researcher at Colorado State University, joins us today to discuss his work “Detecting Climate Signals using Explainable AI with Single Forcing Large Ensembles.”
Works Mentioned
“Detecting Climate Signals using Explainable AI with Single Forcing Large Ensembles”
by Zachary M. Labe, Elizabeth A. Barnes

Sponsored by:
Astrato
and
BBEdit by Bare Bones Software

Direct download: explainable-climate-science.mp3
Category:general -- posted at: 8:24am PDT

Erin Boyle, the Head of Data Science at Myst AI, joins us today to talk about her work with Myst AI, a time series forecasting platform and service with the objective for positively impacting sustainability.

https://docs.myst.ai/docs Visit Weights and Biases at wandb.me/dataskeptic Find Better Data Faster with Nomad Data. Visit nomad-data.com

Direct download: energy-forecasting-pipelines.mp3
Category:general -- posted at: 6:00am PDT

Sean Law, Principle Data Scientist, R&D at a Fortune 500 Company, comes on to talk about his creation of the STUMPY Python Library.

Sponsored by Hello Fresh and mParticle:

Go to Hellofresh.com/dataskeptic16 for up to 16 free meals AND 3 free gifts!

Visit mparticle.com to learn how teams at Postmates, NBCUniversal, Spotify, and Airbnb use mParticle’s customer data infrastructure to accelerate their customer data strategies.

Direct download: matrix-profiles-in-stumpy.mp3
Category:general -- posted at: 6:00am PDT

Data scientists and psychics have at least one major thing in common. Both professions attempt to predict the future. In the case of a data scientist, this is done using algorithms, data, and often comes with some measure of quality such as a confidence interval or estimated accuracy. In contrast, psychics rely on their intuition or an appeal to the supernatural as the source for their predictions. Still, in the interest of empirical evidence, the quality of predictions made by psychics can be put to the test.

The Great Australian Psychic Prediction Project seeks to do exactly that. It's the longest known project tracking annual predictions made by psychics, and the accuracy of those predictions in hindsight. Richard Saunders, host of The Skeptic Zone Podcast, joins us to share the results of this decadal study.

Read the full report: https://www.skeptics.com.au/2021/12/09/psychic-project-full-results-released/

And follow the Skeptics Zone: https://www.skepticzone.tv/

 

Direct download: the-great-australian-prediction-project.mp3
Category:general -- posted at: 6:30pm PDT

Georgia Papacharalampous, Researcher at the National Technical University of Athens, joins us today to talk about her work “Probabilistic water demand forecasting using quantile regression algorithms.”

Visit Springboard and use promo code DATASKEPTIC to receive a $750 discount

Direct download: water-demand-forecasting.mp3
Category:general -- posted at: 9:30am PDT

John Watson, Principal Software Engineer at Splunk, joins us today to talk about Splunk and OpenTelemetry.

 

Direct download: open-telemetry.mp3
Category:general -- posted at: 6:00am PDT

1