Our goal is to make Google Cloud the best place for developers, and Google I/O is one of our favorite ways to spend quality time with the developer community to better understand your needs and challenges. During I/O, we provided a number of breakout sessions aimed at supporting you as you build on Google Cloud, and these are all recorded so that anyone–not just I/O attendees–can learn more and uplevel their skills.
Below are five of our favorite Google Cloud sessions from this year. We’ve ordered these from introductory to advanced, so you can move at your own pace. Start with the basics, then work up to expert topics like building your own machine learning model.
1. Google Cloud Platform (GCP) Essentials
From compute to storage to databases, to say nothing of things like continuous integration tools, DevOps, and machine learning, Google Cloud provides so many options, but not everyone knows where to begin. This session gives you a complete overview of GCP and will leave you with an understanding of the tools available to meet your needs and how to get started.
2. Code, Build, Run, and Observe with Google Cloud
Creating great backend services requires great tools and infrastructure, and our goal with GCP has always been to give developers the resources they need to build. This session offers an overview of GCP products that make it easy to code, build, run, and observe your applications and services with Google Cloud.
3. Making the Right Decisions for Your Serverless Architecture
Chomping at the bit to build a complete end-to-end service entirely on serverless technologies? There are many things you might want to keep in mind as you’re building. This session explains the thought process and methodology we use inside Google, and introduces the constraints of working in environments without persistence.
4. Train Custom Machine Learning Models with No Data Science Expertise
Want to create high quality custom machine learning models but are not an ML expert? Cloud AutoML leverages Google’s state-of-the-art neural architecture search technology to help you do exactly that. Learn how to build and deploy with AutoML Tables, AutoML Video Intelligence, and AutoML Natural Language–and even see how AutoML would fare if it were to participate in data science competitions.
5. Live Coding a Machine Learning Model from Scratch
Far and away our most popular cloud session at this year’s I/O, developer advocate Sara Robinson takes you from an empty Colab notebook to using TensorFlow and Keras to code a model, then training, deploying to Cloud AI Platform for serving, and generating predictions. This is an excellent session for anyone interested in building a machine learning model using Jupyter notebook, and serving the model in production with ease.
Want more? You can find recordings of all our Google Cloud sessions at I/O here.