Standard industry tools on Google Cloud

In addition to Google Cloud’s own data science tools that we’ve been describing so far in this chapter, you can also use other data science tools such as open source frameworks or other popular industry solutions. There are lots of great libraries out there that make it easy to perform the various tasks in the model development life cycle. When it comes to data exploration and processing, for example, the beloved pandas library is a staple of any ML and data analysis course. You can use it for handling missing data, slicing, subsetting, reshaping, merging, and joining datasets. Matplotlib is right up there with pandas for data exploration as it allows you to visualize your data via customizable and interactive plots and charts that can be exported into various file formats. NumPy allows you to easily manipulate and play around with the kinds of n-dimensional arrays and vectors we find in so many ML implementations. Learning NumPy...