Data Science

The technology landscape for data science tools is huge and gets better day by day. Throw in big data, artificial intelligence and several more terms and you get a broader landscape of tools, libraries and frameworks. Dive deep into data science technologies, including Spark, TensorFlow, Jupyter Notebook etc. Under this focus area you will explore the use of analytics in the production environment particularly when creating data pipelines and deploying code.

Under Data Science


How to choose a NoSQL database looking at the technology capabilities and limitations

Implementing Multi-Node Airflow Cluster with HDP Ambari and Celery for Data Pipelines

What are the challenges when setting up Multi-Node Airflow Cluster

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