Google I/O 2022, Google's largest developer conference, kicked off with a keynote speech from Alphabet CEO Sundar Pichai. The keynote speech had major announcements including the launch of Pixel watch, updates on PaLM and LaMDA, advancements in AR and immersive technology etc. Let us look at the key highlights. "Recently we announced plans to invest USD 9.5 billion in data centers and offices across the US. One of our state-of-the-art data centers is in Mayes County, Oklahoma. I'm excited to announce that, there, we are launching the world's largest, publicly-available machine learning hub for our Google Cloud customers," Sundar Pichai said.

Skills in deep learning are in great demand, although these skills can be challenging to identify and to demonstrate. Explaining that you are familiar with a technique or type of problem is very different to being able to use it effectively with open source APIs on real datasets. Perhaps the most effective way of demonstrating skill as a deep learning practitioner is by developing models. A practitioner can practice on standard publicly available machine learning datasets and build up a portfolio of completed projects to both leverage on future projects and to demonstrate competence. In this post, you will discover how you can use small projects to demonstrate basic competence for using deep learning for predictive modeling.