Search Results for 'felienne'
Episode 443: Shawn Wildermuth on Diversity and Inclusion in the Workplace
Shawn Wildermuth of The Hello World film discusses diversity and inclusivity in software development. Host Felienne spoke with Wildermuth about why diversity matters to make better software, and how teams can create a culture in which more people feel welcome and safe. They also discuss how to do code reviews, feedback sessions and job interviews […]
Episode 431: Ken Youens-Clark on Learning Python
Ken Youens-Clark, author of Tiny Python Projects discusses Python. Felienne spoke with Youens-Clark about new features in Python, including optional typing and immutable datatypes. They also discussed Youens-Clark’s upcoming book on how to teach Python and testing. Should testing be taught to new programmers from the start, and how to do that? Contexts for programming […]
Episode 430: Marco Faella on Seriously Good Software
Marco Faella, author of Seriously Good Software discusses how to create good software, using six different ‘qualities’ of code. Felienne spoke with Faella about reliability, space and time complexity, readability, reusability, and thread safety. They also discussed how these qualities are often at odds with each other when creating software, and how to deal with […]
Episode 412: Sam Gavis-Hughson on Technical Interviews
Sam Gavis-Hughson if BytebyByte discusses technical interviews. Felienne spoke with Gavis-Hughson about how to prepare for the dreaded ‘whiteboard interview’ and how to get better at doing interviews. They also discussed the interviewer side of things: how to conduct these interviews yourself and how to improve that. Related Links Dynamic Programming e-book Pramp Interviewing.io Cracking […]
Episode 408: Mike McCourt on Voice and Speech Analysis
Mike McCourt of Invoca discusses how to automatically process and analysis voice data to classify it using machine learning. Felienne spoke with McCourt about the difficulties in processing audio of different qualities, in different languages and the applicability of different types of machine learning to voice data. Related Links Kaldi Mozilla DeepSpeech Invoca engineering blog […]
