Tools

Notes for Tools of Data Science: Git, Command Line, Notebook, AWS etc

21 Data Processing - (Py)Spark

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Summary: Processing Data using (Py)Spark
Pages: 9

6 Some ML Workflow Frameworks

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Summary: Managing workflows in machine learning projects is not trivial.
Pages: 9

5 Git

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Summary: git the tool you need for your everyday work
Pages: 9

4 Terminal

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Summary: work more efficiently
Pages: 9

3 GNUPlot

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References: - GNUPLOT
Summary: quickly make a graph in your command line
Pages: 9

2 Amazon CloudWatch Logs

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Tags:
Summary: CloudWatch logs as a tool for pipeline logs
Pages: 9

1 Jupyter Notebook

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Category: { Tools }
Summary: Jupyter Notebook is a useful tool for data scientists
Pages: 9