Best Bayesianism podcasts we could find (Updated March 2019)
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Data Skeptic
Weekly
 
Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short tutorials and interviews with domain experts.
 
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Talking Machines
Monthly
 
Talking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Neil Lawrence, bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions. Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what to do with the answers.
 
Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions which wi ...
 
Explore data science, analytics, big data, machine learning as we discuss these topics
 
Where did the Nazca Lines come from? Who built Stonehenge, and what secrets lie concealed within Egypt's pyramids? To find out, join the NakedArchaeologists as they undress the past...
 
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show series
 
Bilingual evaluation understudy (or BLEU) is a metric for evaluating the quality of machine translation using human translation as examples of acceptable quality results. This metric has become a widely used standard in the research literature. But is it the perfect measure of quality of machine translation?…
 
Yes, the title is click bait. Yes, we talk about someone who found a strategy to win at Gambling. Yes, we weren’t those people. In those show we talk about the following: Jordy hits a student loan milestone. April 15th is around the corner and we talk about our tax situation; tax man always gets their share. In light for all of these bills, we ...…
 
While at NeurIPS 2018, Kyle chatted with Liang Huang about his work with Baidu research on simultaneous translation, which was demoed at the conference.
 
In episode five of season five we talk about the Stu Hunter conference, Summer schools options (DLRLSS!) and chat with Adrian Weller of the Alan Turing Institute
 
How do you make a computer program understand a language, a natural language, like English? Can we create a program that can create sentences, paragraphs, articles, or stories? In this episode, we explore the basics of Natural Language Processing from Prem Ganeshkumar who is a Lead Natural Language Processing Research Engineer at Agolo in New Y ...…
 
Machine transcription (the process of translating audio recordings of language to text) has come a long way in recent years. But how do the errors made during machine transcription compare to the errors made by a human transcriber? Find out in this episode!
 
At Antonio’s latest visit to the Motor Vehicle Commission, he finds out two things. First, sometimes it’s hard to change data once a mistaken occurs. Second, he will take flight before a fight. We then talk about Amazon and the second headquarter that never was. Apparently, Amazon feels like Antonio – they also took flight. With or without Amaz ...…
 
A sequence to sequence (or seq2seq) model is neural architecture used for translation (and other tasks) which consists of an encoder and a decoder. The encoder/decoder architecture has obvious promise for machine translation, and has been successfully applied this way. Encoding an input to a small number of hidden nodes which can effectively be ...…
 
In episode four of season five we talk about Jupyter Notebooks and Neil's dream of a world craft software and devices, we take a listener question about the conversation surrounding Open AI's GPT-2 its announcement and the coverage and we hear an interview with Brooks Paige of the Alan Turing Instiute…
 
Kyle interviews Julia Silge about her path into data science, her book Text Mining with R, and some of the ways in which she's used natural language processing in projects both personal and professional. Related Links https://stack-survey-2018.glitch.me/ https://stackoverflow.blog/2017/03/28/realistic-developer-fiction/…
 
Dr. Noemi Derzsy is currently a Senior Inventive Scientist at AT&T Labs within the Data Science and AI Research organization. In addition to getting to know what her position entailed, we wanted to know how she got there (especially given her Physics background), how she thought about the data science discipline, and where she saw the future of ...…
 
One of the most challenging NLP tasks is natural language understanding and reasoning. How can we construct algorithms that are able to achieve human level understanding of text and be able to answer general questions about it? This is truly an open problem, and one with the bAbI dataset has been constructed to facilitate. bAbI presents a varie ...…
 
In season five episode three we chat about take a listener question about Five Papers for Mike Tipping, take a listener question on AIAI and chat with Eoin O'Mahony of Uber Here are Neil's five papers. What are yours? Stochastic variational inference by Hoffman, Wang, Blei and Paisley http://arxiv.org/abs/1206.7051 A way of doing approximate in ...…
 
In the first half of this episode, Kyle speaks with Marc-Alexandre Côté and Wendy Tay about Text World. Text World is an engine that simulates text adventure games. Developers are encouraged to try out their reinforcement learning skills building agents that can programmatically interact with the generated text adventure games. In the second ha ...…
 
Word2vec is an unsupervised machine learning model which is able to capture semantic information from the text it is trained on. The model is based on neural networks. Several large organizations like Google and Facebook have trained word embeddings (the result of word2vec) on large corpora and shared them for others to use. The key algorithmic ...…
 
In episode two of season five we unpack the Bezos Paradox (TM Neil Lawrence) take a listener question about best papers and chat with Dougal Maclaurin of Google Brain.
 
In this episode, we interview Dr. Haftan Eckholdt – Chief Data Officer & Chief Science Officer at Understood.org. Understand’s goal is to help the millions of parents whose children, ages 3–20, are struggling with learning and attention issues. Haftan takes us through his journey from rigging computers for distributed computing to generating mo ...…
 
In a recent paper, Leveraging Discourse Information Effectively for Authorship Attribution, authors Su Wang, Elisa Ferracane, and Raymond J. Mooney describe a deep learning methodology for predict which of a collection of authors was the author of a given document.
 
In this episode, we explain the proper semantic interpretation of the Akaike Information Criterion (AIC) and the Generalized Akaike Information Criterion (GAIC) for the purpose of picking the best model for a given set of training data. The precise semantic interpretation of these model selection criteria is provided, explicit assumptions are p ...…
 
The earliest efforts to apply machine learning to natural language tended to convert every token (every word, more or less) into a unique feature. While techniques like stemming may have cut the number of unique tokens down, researchers always had to face a problem that was highly dimensional. Naive Bayes algorithm was celebrated in NLP applica ...…
 
In episode one of season five we talk about Bit by Bit, take a listener question on machine learning gatherings on the African continent (Deep Learning INDABA! DSA!) and hear an interview with Daphne Koller recorded at ODSC West
 
Jim Savage is the Head of Data Science at @lendableinc He joins us on the show to take us to school about statistics, his company, the work he’s been doing, and cheap noodles. Jordy and Antonio have Jim make sense of this blog post for them: https://khakieconomics.github.io/2017/01/01/Building-useful-models-for-industry.html Along the way, we l ...…
 
Github is many things besides source control. It's a social network, even though not everyone realizes it. It's a vast repository of code. It's a ticketing and project management system. And of course, it has search as well. In this episode, Kyle interviews Hamel Husain about his research into semantic code search.…
 
As data science imposters, we get to think about the history of things that came before 5G or whatever new whizzbang technology. In this episode, we talk about the origins of Morse code and related items. Did you know that you could play songs using an old phone? Check out this site for some ideas: http://www.yak.net/carmen/phone_songs.html We ...…
 
This episode reboots our podcast with the theme of Natural Language Processing for the next few months. We begin with introductions of Yoshi and Linh Da and then get into a broad discussion about natural language processing: what it is, what some of the classic problems are, and just a bit on approaches. Finishing out the show is an interview w ...…
 
Kyle shares a few thoughts on mistakes observed by job applicants and also shares a few procedural insights listeners at early stages in their careers might find value in.
 
Yes. Calculus during a podcast? That’s tricky, bold, dare I say – audacious. However, DSI doesn’t scare easily. Antonio and Jordy put their college maths to the test. While you’re here and still reading we would love to invite you to share with us data that you collect about yourself, your commute, or other aspects of your life. We’d love to do ...…
 
In today's episode, Kyle chats with Alexander Zhebrak, CTO of Insilico Medicine, Inc. Insilico self describes as artificial intelligence for drug discovery, biomarker development, and aging research. The conversation in this episode explores the ways in which machine learning, in particular, deep learning, is contributing to the advancement of ...…
 
Fueled by a few cold IPA beers, a microphone, and a quiet room provided by a friend of the show – the Data Science Imposters grab the mics and have a good conversation. Join the conversation on Twitter @dsimposters
 
At the NeurIPS 2018 conference, Stradigi AI premiered a training game which helps players learn American Sign Language. This episode brings the first of many interviews conducted at NeurIPS 2018. In this episode, Kyle interviews Chief Data Scientist Carolina Bessega about the deep learning architecture used in this project. The Stradigi AI team ...…
 
In this episode, we explore the question of what can computers do as well as what computers can’t do using the Turing Machine argument. Specifically, we discuss the computational limits of computers and raise the question of whether such limits pertain to biological brains and other non-standard computing machines. This episode is dedicated to ...…
 
This week, Kyle interviews Scott Nestler on the topic of Data Ethics. Today, no ubiquitous, formal ethical protocol exists for data science, although some have been proposed. One example is the INFORMS Ethics Guidelines. Guidelines like this are rather informal compared to other professions, like the Hippocratic Oath. Yet not every profession r ...…
 
Kyle interviews Mick West, author of Escaping the Rabbit Hole: How to Debunk Conspiracy Theories Using Facts, Logic, and Respect about the nature of conspiracy theories, the people that believe them, and how to help people escape the belief in false information. Mick is also the creator of metabunk.org. The discussion explores conspiracies like ...…
 
For the end of season four we take a break from our regular format and bring you a talk from Professor Finale Doshi Velez of Harvard University on the possibility of explanation Tune in next season!
 
Can a computer be artistic? If so, how valuable can their pieces of art become? The Obvious Group certainly thinks so and they have made their first sale of a computer generated portrait for $432,000. They’ve done this by doing some great promotion but also leveraging code published on the internet built on GANs (generative adversarial networks).…
 
Fake news attempts to lead readers/listeners/viewers to conclusions that are not descriptions of reality. They do this most often by presenting false premises, but sometimes by presenting flawed logic. An argument is only sound and valid if the conclusions are drawn directly from all the state premises, and if there exists a path of logical rea ...…
 
Fake news can be responded to with fact-checking. However, it's easier to create fake news than the fact check it. Full Fact is the UK's independent fact-checking organization. In this episode, Kyle interviews Mevan Babakar, head of automated fact-checking at Full Fact. Our discussion talks about the process and challenges in doing fact-checkin ...…
 
In episode twenty one of season four we talk about distributed intelligence systems (mainly those internal to humans), talk about what were excited to see at the Conference on Neural Information Processing Systems and in advance of our trek to Canada we chat with Garth Gibson president and CEO of the Vector Institute.…
 
In mathematics, truth is universal. In data, truth lies in the where clause of the query. As large organizations have grown to rely on their data more significantly for decision making, a common problem is not being able to agree on what the data is. As the volume and velocity of data grow, challenges emerge in answering questions with precisio ...…
 
In mathematics, truth is universal. In data, truth lies in the where clause of the query. As large organizations have grown to rely on their data more significantly for decision making, a common problem is not being able to agree on what the data is. As the volume and velocity of data grow, challenges emerge in answering questions with precisio ...…
 
Fast radio bursts are an astrophysical phenomenon first observed in 2007. While many observations have been made, science has yet to explain the mechanism for these events. This has led some to ask: could it be a form of extra-terrestrial communication? Probably not. Kyle asks Gerry Zhang who works at the Berkeley SETI Research Center about thi ...…
 
In episode twenty of season four we talk about the importance of crediting your data, answer a listener question about internships vs salaried positions and talk with Matt Kusner of the Alan Turing institute the UK’s national institute for data science and AI.
 
Have you seen the movie a beautiful mind? Have you ever been facing jail time if you cooperate against an accomplice? Well, let’s focus on the movie first – there’s a scene where five guys, one of those guys being John Nash, and they are at a bar when a group of women walk in … In the movie, the focus of the men is on the blonde – one of the wo ...…
 
This episode explores the root concept of what it is to be Bayesian: describing knowledge of a system probabilistically, having an appropriate prior probability, know how to weigh new evidence, and following Bayes's rule to compute the revised distribution. We present this concept in a few different contexts but primarily focus on how our bird ...…
 
Jake Kramer joins Jordy and Antonio to display his love for deep space, give background and context of his company, share his thoughts on entrepreneurship, and wow them with some of the technologies he’s been able to explore. Jake Kramer is a managing partner at Fed Tech, a unique private venture program, funded by federal agencies and corporat ...…
 
This is our interview with Dorje Brody about his recent paper with David Meier, How to model fake news. This paper uses the tools of communication theory and a sub-topic called filtering theory to describe the mathematical basis for an information channel which can contain fake news. Thanks to our sponsor Gartner.…
 
In episode nineteen of season four we talk about causality in the real world, take a question about being surprised by the elephant in the room and talk with Kush Varshney of IBM.
 
Without getting into definitions, we have an intuitive sense of what a "community" is. The Louvain Method for Community Detection is one of the best known mathematical techniques designed to detect communities. This method requires typical graph data in which people are nodes and edges are their connections. It's easy to imagine this data in th ...…
 
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