An Introduction to Cloud Composer

Workflows are a common theme in data analytics – they involve ingesting, transforming, and analyzing data to figure out the meaningful information within. In Google Cloud Platform (GCP), the tool for hosting workflows is Cloud Composer which is a hosted version of the popular open source workflow tool Apache Airflow. Setup and requirements log in…

Machine Learning with Spark on Google Cloud Dataproc

In this post you will learn how to implement logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset. Google Cloud DataprocĀ is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a…

How to Use AutoML and Vision API in GCP

What is the Vision API and what can it do? The vision API is an API that uses machine learning and other Google services to extract information from images. The sorts of predictions that it can currently make include but are not limited to the following list: Label Detection, which is used to detect the…

Recommend Products using ML with Cloud SQL and Dataproc

As our goal is to provide demo that is why we are using the Cloud SQL or else yo can use spanner for horizontal scaling. our goal is to Create Cloud SQL instance Create database tables by importing .sql files from Cloud Storage Populate the tables by importing .csv files from Cloud Storage Allow access…

How To Set up a Development Environment in Python in Google Cloud

In this blog, you set up a Python development environment on Google Cloud Platform, using Google Compute Engine to create a virtual machine (VM) and installing software libraries for software development. You perform the following tasks: Provision a Google Compute Engine instance. Connect to the instance using SSH. Install a Python library on the instance….

Cloud ML Engine Your Friend on cloud

What we are doing here. Theory of Not relativity but cloud ml engine a bit of tensorflow(not stack overflow) and hands on in Create a TensorFlow training application and validate it locally. Run your training job on a single worker instance in the cloud. Run your training job as a distributed training job in the…

Analyzing Financial Time Series Using BigQuery and Cloud Datalab

This solution illustrates the power and utility of BigQuery and Cloud Datalab as tools for quantitative analysis. The solution provides an introduction (this document) and gets you set up to run a notebook-based Cloud Datalab tutorial. If you’re a quantitative analyst, you use a variety of tools and techniques to mine big data, such as market transaction histories, for…