Alle afleveringen
612 afleveringen, van nieuw naar oud
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Power K-Means
7 maart 2022 · 33 min
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. Lees meer
Click here to access additional show notes on our website!
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Explainable K-Means
3 maart 2022 · 26 min
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. Lees meer
Check out our website for extended show notes!
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Customer Clustering
28 februari 2022 · 22 min
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. Lees meer
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.
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k-means Image Segmentation
22 februari 2022 · 23 min
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. Lees meer
Check out our website for extended show notes and images!
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Nomad DataIn 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.
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Tracking Elephant Clusters
18 februari 2022 · 26 min
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. Lees meer
Click here to see additional show notes on our website!
Thanks to our sponsor, Astrato
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k-means clustering
14 februari 2022 · 24 min
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. Lees meer
This episode is an overview of the topic presented in several segments.
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Snowflake Essentials
7 februari 2022 · 47 min
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." Lees meer
Snowflake Essentials: Getting Started with Big Data in the Cloud by Frank Bell, Raj Chirumamilla, Bhaskar B. Joshi, Bjorn Lindstrom, Ruchi Soni, Sameer Videkar
Snowflake Solutions
Snoptimizer - Snowflake Cost, Security, and Performance Optimization - Coming Soon!
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Explainable Climate Science
31 januari 2022 · 35 min
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 Lees meerSponsored by:
Astrato
and
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Energy Forecasting Pipelines
24 januari 2022 · 43 min
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. Lees meer
https://docs.myst.ai/docs Visit Weights and Biases at wandb.me/dataskeptic Find Better Data Faster with Nomad Data. Visit nomad-data.com
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Matrix Profiles in Stumpy
17 januari 2022 · 39 min
Sean Law, Principle Data Scientist, R&D at a Fortune 500 Company, comes on to talk about his creation of the STUMPY Python Library. Lees meer
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.
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The Great Australian Prediction Project
14 januari 2022 · 25 min
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. Lees meer
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/
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Water Demand Forecasting
10 januari 2022 · 26 min
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." Lees meer
Visit Springboard and use promo code DATASKEPTIC to receive a $750 discount
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Open Telemetry
3 januari 2022 · 36 min
John Watson, Principal Software Engineer at Splunk, joins us today to talk about Splunk and OpenTelemetry.
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Fashion Predictions
27 december 2021 · 35 min
Yusan Lin, a Research Scientist at Visa Research, comes on today to talk about her work "Predicting Next-Season Designs on High Fashion Runway."
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Time Series Mini Episodes
25 december 2021 · 37 min
Time series topics on Data Skeptic predate our current season. This holiday special collects three popular mini-episodes from the archive that discuss time series topics with a few new comments from Kyle.
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Forecasting Motor Vehicle Collision
20 december 2021 · 39 min
Dr. Darren Shannon, a Lecturer in Quantitative Finance in the Department of Accounting and Finance, University of Limerick, joins us today to talk about his work "Extending the Heston Model to Forecast Motor Vehicle Collision Rates."
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Deep Learning for Road Traffic Forecasting
13 december 2021 · 32 min
Eric Manibardo, PhD Student at the University of the Basque Country in Spain, comes on today to share his work, "Deep Learning for Road Traffic Forecasting: Does it Make a Difference?"
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Bike Share Demand Forecasting
6 december 2021 · 41 min
Daniele Gammelli, PhD Student in Machine Learning at Technical University of Denmark and visiting PhD Student at Stanford University, joins us today to talk about his work "Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management." Lees meer
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Forecasting in Supply Chain
29 november 2021 · 36 min
Mahdi Abolghasemi, Lecturer at Monash University, joins us today to talk about his work "Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion."
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Black Friday
26 november 2021 · 45 min
The retail holiday "black Friday" occurs the day after Thanksgiving in the United States. It's dubbed this because many retail companies spend the first 10 months of the year running at a loss (in the red) before finally earning as much as 80% of their revenue in the last two months of the year. Lees meer
This episode features four interviews with guests bringing unique data-driven perspectives on the topic of analyzing this seeming outlier in a time series dataset.
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Aligning Time Series on Incomparable Spaces
22 november 2021 · 34 min
Alex Terenin, Postdoctoral Research Associate at the University of Cambridge, joins us today to talk about his work "Aligning Time Series on Incomparable Spaces."
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Comparing Time Series with HCTSA
15 november 2021 · 43 min
Today we are joined again by Ben Fulcher, leader of the Dynamics and Neural Systems Group at the University of Sydney in Australia, to talk about hctsa, a software package for running highly comparative time-series analysis.
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Change Point Detection Algorithms
8 november 2021 · 31 min
Gerrit van den Burg, Postdoctoral Researcher at The Alan Turing Institute, joins us today to discuss his work "An Evaluation of Change Point Detection Algorithms."
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Time Series for Good
1 november 2021 · 38 min
Bahman Rostami-Tabar, Senior Lecturer in Management Science at Cardiff University, joins us today to talk about his work "Forecasting and its Beneficiaries."
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Long Term Time Series Forecasting
25 oktober 2021 · 38 min
Alex Mallen, Computer Science student at the University of Washington, and Henning Lange, a Postdoctoral Scholar in Applied Math at the University of Washington, join us today to share their work "Deep Probabilistic Koopman: Long-term Time-Series Forecasting Under Periodic Uncertainties." Lees meer
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Fast and Frugal Time Series Forecasting
17 oktober 2021 · 38 min
Fotios Petropoulos, Professor of Management Science at the University of Bath in The U.K., joins us today to talk about his work "Fast and Frugal Time Series Forecasting."
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Causal Inference in Educational Systems
11 oktober 2021 · 41 min
Manie Tadayon, a PhD graduate from the ECE department at University of California, Los Angeles, joins us today to talk about his work "Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach."
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Boosted Embeddings for Time Series
4 oktober 2021 · 29 min
Sankeerth Rao Karingula, ML Researcher at Palo Alto Networks, joins us today to talk about his work "Boosted Embeddings for Time Series Forecasting." Lees meer
Works Mentioned
Boosted Embeddings for Time Series Forecasting
by Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahmasbi, Mehrnaz Amjadi, Deokwoo Jung, Ricky Si, Charanraj Thimmisetty, Luisa Polania Cabrera, Marjorie Sayer, Claudionor Nunes Coelho Jrhttps://www.linkedin.com/in/sankeerthrao/
https://twitter.com/sankeerthrao3
https://lod2021.icas.cc/
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Change Point Detection in Continuous Integration Systems
27 september 2021 · 34 min
David Daly, Performance Engineer at MongoDB, joins us today to discuss "The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System". Lees meer
Works Mentioned
The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System
by David Daly, William Brown, Henrik Ingo, Jim O'Leary, David BradfordSocial MediaDavid's Website
David's Twitter
Mongodb -
Applying k-Nearest Neighbors to Time Series
20 september 2021 · 24 min
Samya Tajmouati, a PhD student in Data Science at the University of Science of Kenitra, Morocco, joins us today to discuss her work Applying K-Nearest Neighbors to Time Series Forecasting: Two New Approaches.
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Ultra Long Time Series
13 september 2021 · 28 min
Dr. Feng Li, (@f3ngli) is an Associate Professor of Statistics in the School of Statistics and Mathematics at Central University of Finance and Economics in Beijing, China. He joins us today to discuss his work Distributed ARIMA Models for Ultra-long Time Series. Lees meer
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MiniRocket
6 september 2021 · 26 min
Angus Dempster, PhD Student at Monash University in Australia, comes on today to talk about MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification, a fast deterministic transform for time series classification. MINIROCKET reformulates ROCKET, gaining a 75x improvement on larger datasets with essentially the same performance. In this episode, we talk about the insights that realized this speedup as well as use cases. Lees meer
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ARiMA is not Sufficient
30 augustus 2021 · 23 min
Chongshou Li, Associate Professor at Southwest Jiaotong University in China, joins us today to talk about his work Why are the ARIMA and SARIMA not Sufficient.
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Comp Engine
23 augustus 2021 · 36 min
Ben Fulcher, Senior Lecturer at the School of Physics at the University of Sydney in Australia, comes on today to talk about his project Comp Engine. Lees meer
Follow Ben on Twitter: @bendfulcher
For posts about time series analysis : @comptimeseries
comp-engine.org -
Detecting Ransomware
16 augustus 2021 · 31 min
Nitin Pundir, PhD candidate at University Florida and works at the Florida Institute for Cybersecurity Research, comes on today to talk about his work "RanStop: A Hardware-assisted Runtime Crypto-Ransomware Detection Technique." Lees meer
FICS Research Lab - https://fics.institute.ufl.edu/
LinkedIn - https://www.linkedin.com/in/nitin-pundir470/
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GANs in Finance
9 augustus 2021 · 23 min
Florian Eckerli, a recent graduate of Zurich University of Applied Sciences, comes on the show today to discuss his work Generative Adversarial Networks in Finance: An Overview.
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Predicting Urban Land Use
2 augustus 2021 · 27 min
Today on the show we have Daniel Omeiza, a doctoral student in the computer science department of the University of Oxford, who joins us to talk about his work Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa. Lees meer
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Opportunities for Skillful Weather Prediction
26 juli 2021 · 34 min
Today on the show we have Elizabeth Barnes, Associate Professor in the department of Atmospheric Science at Colorado State University, who joins us to talk about her work Identifying Opportunities for Skillful Weather Prediction with Interpretable Neural Networks. Find more from the Barnes Research Group on their site. Lees meer
Weather is notoriously difficult to predict. Complex systems are demanding of computational power. Further, the chaotic nature of, well, nature, makes accurate forecasting especially difficult the longer into the future one wants to look. Yet all is not lost!
In this interview, we explore the use of machine learning to help identify certain conditions under which the weather system has entered an unusually predictable position in it's normally chaotic state space.
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Predicting Stock Prices
19 juli 2021 · 34 min
Today on the show we have Andrea Fronzetti Colladon (@iandreafc), currently working at the University of Perugia and inventor of the Semantic Brand Score, joins us to talk about his work studying human communication and social interaction. Lees meer
We discuss the paper Look inside. Predicting Stock Prices by Analyzing an Enterprise Intranet Social Network and Using Word Co-Occurrence Networks.
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N-Beats
12 juli 2021 · 34 min
Today on the show we have Boris Oreshkin @boreshkin, a Senior Research Scientist at Unity Technologies, who joins us today to talk about his work N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting. Lees meer
Works Mentioned:
N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting
By Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
https://arxiv.org/abs/1905.10437Social Media
LinkedinTwitter
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Translation Automation
6 juli 2021 · 36 min
Today we are back with another episode discussing AI in the work field. AI has, is, and will continue to facilitate the automation of work done by humans. Sometimes this may be an entire role. Other times it may automate a particular part of their role, scaling their effectiveness. Lees meer
Carl Stimson, a Freelance Japanese to English translator, comes on the show to talk about his work in translation and his perspective about how AI will change translation in the future.
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Time Series at the Beach
28 juni 2021 · 23 min
Shane Ross, Professor of Aerospace and Ocean Engineering at Virginia Tech University, comes on today to talk about his work "Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation."
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Automatic Identification of Outlier Galaxy Images
21 juni 2021 · 36 min
Lior Shamir, Associate Professor of Computer Science at Kansas University, joins us today to talk about the recent paper Automatic Identification of Outliers in Hubble Space Telescope Galaxy Images. Lees meer
Follow Lio on Twitter @shamir_lior
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Do We Need Deep Learning in Time Series
16 juni 2021 · 29 min
Shereen Elsayed and Daniela Thyssens, both are PhD Student at Hildesheim University in Germany, come on today to talk about the work "Do We Really Need Deep Learning Models for Time Series Forecasting?"
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Detecting Drift
11 juni 2021 · 27 min
Sam Ackerman, Research Data Scientist at IBM Research Labs in Haifa, Israel, joins us today to talk about his work Detection of Data Drift and Outliers Affecting Machine Learning Model Performance Over Time. Lees meer
Check out Sam's IBM statistics/ML blog at: http://www.research.ibm.com/haifa/dept/vst/ML-QA.shtml
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Darts Library for Time Series
31 mei 2021 · 25 min
Julien Herzen, PhD graduate from EPFL in Switzerland, comes on today to talk about his work with Unit 8 and the development of the Python Library: Darts.
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Forecasting Principles and Practice
24 mei 2021 · 32 min
Welcome to Timeseries! Today's episode is an interview with Rob Hyndman, Professor of Statistics at Monash University in Australia, and author of Forecasting: Principles and Practices.
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Prequisites for Time Series
21 mei 2021 · 9 min
Today's experimental episode uses sound to describe some basic ideas from time series. Lees meer
This episode includes lag, seasonality, trend, noise, heteroskedasticity, decomposition, smoothing, feature engineering, and deep learning.
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Orders of Magnitude
7 mei 2021 · 33 min
Today's show in two parts. First, Linhda joins us to review the episodes from Data Skeptic: Pilot Season and give her feedback on each of the topics. Lees meer
Second, we introduce our new segment "Orders of Magnitude". It's a statistical game show in which participants must identify the true statistic hidden in a list of statistics which are off by at least an order of magnitude. Claudia and Vanessa join as our first contestants. Below are the sources of our questions.
Heights
https://en.wikipedia.org/wiki/Willis_Tower
https://en.wikipedia.org/wiki/Eiffel_Tower
https://en.wikipedia.org/wiki/GreatPyramidof_Giza
https://en.wikipedia.org/wiki/InternationalSpaceStation
Bird Statistics
Birds in the US since 2000
Causes of Bird Mortality
Amounts of Data
Our statistics come from this post
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They're Coming for Our Jobs
3 mei 2021 · 44 min
AI has, is, and will continue to facilitate the automation of work done by humans. Sometimes this may be an entire role. Other times it may automate a particular part of their role, scaling their effectiveness. Unless progress in AI inexplicably halts, the tasks done by humans vs. machines will continue to evolve. Today's episode is a speculative conversation about what the future may hold. Lees meer
Co-Host of Squaring the Strange Podcast, Caricature Artist, and an Academic Editor, Celestia Ward joins us today! Kyle and Celestia discuss whether or not her jobs as a caricature artist or as an academic editor are under threat from AI automation.
Mentions
https://squaringthestrange.wordpress.com/
https://twitter.com/celestiaward
The legendary Dr. Jorge Pérez and his work studying unicorns
Supernormal stimulus
International Society of Caricature Artists
Two Heads Studios