The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
Applying k-Nearest Neighbors to Time Series
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.
Ultra Long Time Series
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.
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.
ARiMA is not Sufficient
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.
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.
Follow Ben on Twitter: @bendfulcher
For posts about time series analysis : @comptimeseries
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.”
FICS Research Lab - https://fics.institute.ufl.edu/
LinkedIn - https://www.linkedin.com/in/nitin-pundir470/
Professional and informative
The thing I like most about this podcast is the professionalism - the host, Kyle, always keep the content professional and impartial, allowing the listener to focus on the science rather than lecturing the listener. The content is also Dell big technically to serve as an introduction to many methods in ML
I also want to leave a five star review to counterbalance the fool who left a one star review because the host has not made a comment about BLM! This is a podcast about machine learning and AI. I’m grateful for this excellent resource and the huge amount of work that obviously goes into it.
Just listened to Kyle speaking with Adrian Martin about CNN and cutting edge advancements in neural nets. Love getting this insiders perspective.