Spyder, that stands for Scientific Python Development
Environment is very popular among engineers, scientists, and data analysts for
machine learning and data science purpose. It’s powerful scientific environment
is written in Python and is also meat for Python development. It supports
editing, debugging, analysis and profiling functionality for an amazing too for
data science purpose.
It has built-in popular libraries like Numpy, Pandas, SciPy,
IPython, SymPy, QtCOnsole, Matplotlib and many more.
Installation
If you have not downloaded Spyder, then you must read (***) that
will help you set up Machine Learning Environment. Alternatively, you can also
watch the video for the same.
Major Components of Spyder IDE
Your good knowledge and kindness in playing with all the pieces were very useful. I don’t know what I would have done if I had not encountered such a step like this.
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