A stable of data scientists were asked to name five of their most useful tools in persuading raw data to give up its secrets.
Here are their answers (in quotes) as compiled by Ericka Chickowski on SearchBusinessAnalytics.com:
1. Python. “Not so much a distinct piece of software as much as a programmatic means for creating custom algorithms, Python is the go-to for many data scientists.”
2. R. “R is another programming language that many data science professionals depend on, though it is a little simpler and more purpose-built for data science.”
3. Jupyter Notebook. “Jupyter Notebook supports R and Python with great library support for data access and visualizations…Jupyter Notebook is a great tool to prototype models interactively.”
4. Tableau. “It’s the fastest data visualization tool and business intelligence [tool] in evolution. It is very quick to implement, easy to learn and very intuitive to use.”
5. Keras. “Keras is an open source neural network library written in Python to enable fast experimentation with deep neural networks, and [it] is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit or Theano.”
