Summary
1. Summary
SPEAKER: Back to the original question for this module-- what options do you have for building an AI project or an ML model? Do you have the answer now? If not, let's take a quick look. Google Cloud offers a wealth of options to suit your needs, whether you're a business user, data scientist, developer, or ML engineer. These range from no-code out-of-the-box solutions to low-code tools, and even code-based DIY approaches. You've been introduced to Vertex AI, Google's unified AI platform, which serves as your ultimate workspace for exploring these options and building end-to-end machine learning projects. You've specifically focused on AutoML, a fantastic low- or no-code tool within Vertex AI that automates ML development from data preparation to model training and serving, all using your own data. Pre-trained APIs-- ready-made solutions that leverage powerful pre-trained machine learning models, completely eliminating the need for any training data. Custom training-- this empowers you to manually code ML projects using versatile tools such as Python, Jax, and Vertex AI Workbench. Given all these exciting options, how do you build an ML model step by step on Vertex AI? Let's uncover the answer in the next module. See you soon!2. Let's practice!
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