By Russell Jurney
Data technological know-how groups seeking to flip examine into precious analytics functions require not just the precise instruments, but in addition the appropriate technique if they’re to prevail. With the revised moment variation of this hands-on advisor, up-and-coming info scientists will find out how to use the Agile info technological know-how improvement method to construct information functions with Python, Apache Spark, Kafka, and different tools.
Author Russell Jurney demonstrates tips on how to compose an information platform for development, deploying, and refining analytics functions with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll study an iterative procedure that allows you to speedy swap the type of research you’re doing, counting on what the knowledge is telling you. post info technology paintings as an internet program, and have an effect on significant swap on your organization.
- Build worth out of your info in a chain of agile sprints, utilizing the data-value pyramid
- Extract beneficial properties for statistical versions from a unmarried dataset
- Visualize facts with charts, and disclose diverse points via interactive reports
- Use ancient facts to foretell the long run through category and regression
- Translate predictions into actions
- Get suggestions from clients after each one dash to maintain your venture on track
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Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark by Russell Jurney