nbmanips allows you easily manipulate ipynb files
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Updated
Mar 6, 2024 - Python
nbmanips allows you easily manipulate ipynb files
The primary objective of this study is to explore the feasibility of using machine learning algorithms to classify health insurance plans based on their coverage for routine dental services. To achieve this, I used six different classification algorithms: LR, DT, RF, GBT, SVM, FM(Tech: PySpark, SQL, Databricks, Zeppelin books, Hadoop, Spark-Submit)
Heart disease classification with data mining(Zeppelin Notebook)
Data Mining Census ECON using Apache Spark
Qubole Delta Lake Spark Streaming ingestion end to end Demo
A wrapper for ze2nb to be used as a CLI
Real-Time & Batch Data Processing Pipeline
Apache Spark 2.2.0 Docker image
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