Random thoughts about random subjects… From science to literature and between manga and watercolours, passing by data science and rugby; including film, physics and fiction, programming, pictures and puns.
I had an opportunity to be one of the panellists in the Data Skeptic podcast recently. It was great to have been invited and as a listener to the podcast it was a really treat to be able to take part. Also, recording it was fun…
In the episode Kyle talks about the relationship between Covid-19 and Carbon Emissions. George tells us about the new Hateful Memes Challenge from Facebook. Lan joins us to talk about Google’s AI Explorables. I talk about a paper that uses neural networks to detect infections in the ear.
During the weekend I got a member of the team getting in touch because he was unable to get a Python package working for him . He had just installed Python in his machine, but things were not quite right… For example pip was not working and he had a bit of a bother setting some environment variables… I recommended to him having a look at installing Python via the Anaconda distribution. Today he was up and running with his app.
Given that outcome, I thought it was a great coincidence that the latest episode of Talk Python To Me that started playing on my way back home happened to be about Conda and Conda-Forge. I highly recommend listening to it. Take a loook:
Have you ever had trouble installing a package you wanted to use in your Python app? Likely it contained some odd dependency, required a compilation step, maybe even using an uncommon compiler like Fortran. Did you try it on Windows? How many times have you seen “Cannot find vcvarsall.bat” before you had to take a walk?
If this sounds familiar, you might want to check conda the package manager, Anaconda, the distribution, conda forge, and conda build. They dramatically lower the bar for installing packages on all the platforms.
This week you’ll meet Phil Elson, Kale Franz, and Michael Sarahan who all work on various parts of this ecosystem.
I have been having a break from creating the Quantum Tunnel Podcast. Partly this was because I did not have a suitable replacement to host the material after Apple got rid of MobileMe and sites… Then I just didn’t have that much time. I will pick it up one of these days… Do remind me please.
Nonetheless, my podcast listening has continued and I get my fix from the likes of the excellent RadioLab podcast, Freakonomics and even More or Less. Recently I have started collecting podcasts that talk about data science and machine learning and here are some examples of what has hit my podcast list:
Data Stories is a great chat forum between Enrico Bertini and Moritz Stefaner plus guests; really interesting guests! The main focus is data visualisation but they chat about all sorts of related topics.
The Data Skeptic ranges from 10 minute conversations between Kyle Polich and his wife Linda, trying to elucidate concepts and areas of interest in statistics, machine learning, probability and others, through to interviews/chats with guests. Worth checking out!
Covering information about machine learning and data science, this podcast is brought to us by Udacity’s Ben Jaffe and Katie Malone. Weekly episodes will keep you well informed.
I really enjoy the conversations that Katherine Gorman and Ryan Adams have regarding topics around machine learning. I like the question and answer session where listeners can send their queries. Interesting guests and always fun to listen to
I recently heard about this podcast and just downloaded the latest episode but have not had a chance to hear it. I assume that the information will be as interesting as other O’Reilly’s outlets. Looking forward to hearing what Ben Lorica has to say!
Why would you not listen to a podcast with such a cool name? Besides, Jonathon Morgan and Chris Albon chat over a beer is a good fun way to hear about the latest and greatest in the data science and technology arena.
In the best style of a 101 course, this podcast addresses questions such as how do devices that use machine learning work? How can they get in smarter? What does it take to make them more human-like? Listen to it to find out some answers!
I have been waiting quite a bit for the RFU to make their podcasts available via iTunes or some other similar service. I used to listen to them but for one reason or another the feed changed to the extent that no submission was done to iTunes and the RSS of the RFU’s website is basically dead.
So, inspired by a post by Rolando Garza, I decided to hack an RSS that can actually be used to download the RFU podcast and get some information about Rugby. So I used a combination of Feedity which used HTML scraping to generate an RSS of almost any page. With the help op Yahoo Pipes I managed to use the magic of regular expressions to add appropriate dates and enclosures to the feed and the result is the RFU Podcast Feed.
So, as long as the RFU does not change the way they deal with their website and the posting of their mp3 content, then you can enjoy a bit of Rugby right in your mp3 devices.
