Tag: IEEE CS
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 411: Aaron Vonderhaar on Elm
Aaron Vonderhaar, maintainer and open source contributor to the Elm programming language, talks with host Adam Conrad about the Elm language, its foundations, features, and applications in the front end web development ecosystem. The discussion covers the basics of the language; use cases for Elm; comparisons with JavaScript and JavaScript interoperability; performance, security, and testing […]
Episode 410: Sara Leen on Localizing and Porting Japanese Games
Sara Leen of XSEED Games discusses localizing, porting, and modernizing Japanese games with Jeremy Jung. They discuss what makes games different, learning a codebase, extracting/replacing text, text encoding, replacing art assets, rewriting games, and reverse engineering them. Related Links Personal Website Corpse Party PC Programming Trails in the Sky Programming Trails in the Sky Second […]
Episode 409: Joe Kutner on the Twelve-Factor App
Joe Kutner, Software Architect for Heroku at Salesforce.com, discusses the twelve-factor app. The twelve-factor app is a methodology that aids development of modern apps that are portable, scalable, and maintainable. Host Kanchan Shringi spoke with Kutner about the origin of these principles; their continued and growing importance with advances in microservices, DevOps, and containerization; and […]
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 […]
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