About this episode
Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community. If you’re anything like us, your New Year’s resolutions probably included an AI section, so this week we explore some of the learning resources available for artificial intelligence and deep learning. Where you go with it depends upon what you want to achieve, so we discuss academic versus industry career paths, and try to set you on the Practical AI path that will help you level up. Join the discussion Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today! Sponsors: Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com . Rollbar – We move fast and fix things because of Rollbar. Resolve errors in minutes. Deploy with confidence. Learn more at rollbar.com/changelog . Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Algolia – Our search partner. Algolia’s full suite search APIs enable teams to develop unique search and discovery experiences across all platforms and devices. We’re using Algolia to power our site search here at Changelog.com. Get started for free and learn more at algolia.com . Featuring: Chris Benson – Website , GitHub , LinkedIn , X Daniel Whitenack – Website , GitHub , X Show Notes: Courses Amazon Machine Learning with AWS Google Machine Learning Crash Course with TensorFlow APIs Microsoft Professional Program for Artificial Intelligence Coursera / deeplearning.ai NVIDIA Deep Learning Institute Google, Amazon, Microsoft: How do their free machine-learning courses compare? Stanford Machine Learning Videos on YouTube Books “Deep Learning” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville “Natural Language Processing with PyTorch” by Delip Rao and Brian McMahan “Machine Learning With Go” by Daniel Whitenack and Janani Selvaraj (Daniel is too humble to put his own book in this list, so Chris inserted it above without Daniel’s knowledge - because it’s a damn fine book!) Hybrid resources Machine learning with TensorFlow crash course Intro to deep learning with PyTorch Spinning Up in Deep RL Meetups PyData Atlanta Deep Learning Meetup Something missing or broken? PRs welcome!