By Russell Jurney
Data technological know-how groups trying to flip study into worthwhile analytics functions require not just the fitting instruments, but in addition the perfect procedure if they’re to be successful. With the revised moment version of this hands-on advisor, up-and-coming information scientists will the right way to use the Agile information technology improvement technique to construct info purposes with Python, Apache Spark, Kafka, and different tools.
Author Russell Jurney demonstrates the right way to compose an information platform for construction, deploying, and refining analytics functions with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll research an iterative technique that allows you to fast switch the type of research you’re doing, reckoning on what the knowledge is telling you. put up info technology paintings as an online software, and impact significant switch on your organization.
- Build worth out of your info in a sequence of agile sprints, utilizing the data-value pyramid
- Extract positive aspects for statistical versions from a unmarried dataset
- Visualize information with charts, and disclose diversified points via interactive reports
- Use historic information to foretell the longer term through type and regression
- Translate predictions into actions
- Get suggestions from clients after every 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
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