الصفحة 1
الصفحة 1
Data science on the Google cloud platform : Implementing end-to-end real-time data pipelines : From ingest to machine learning
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. You'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines
Adobe Photoshop CC Classroom in a Book
The 15 project-based lessons show key step-by-step techniques for working in Photoshop, including how to correct, enhance, and distort digital images, create image composites, and prepare images for print and the web. In addition to learning the essential elements of the Photoshop interface, this revised edition for the 2018 release covers features like search capabilities, Content-Aware Crop, Select and Mask, Face-Aware Liquify, designing with multiple artboards, creating and organising enhanced brush presets, and much more!
