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lines changed Original file line number Diff line number Diff line change @@ -828,7 +828,7 @@ handy.
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See also :func: `scipy.optimize.approx_fprime ` to find your errors.
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- Synthetic exercices
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+ Synthetic exercises
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-------------------
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.. |flat_min_0 | image :: auto_examples/images/sphx_glr_plot_exercise_flat_minimum_001.png
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:target: auto_examples/plot_exercise_ill_conditioned.html
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:align: right
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- .. topic :: **Exercice : A simple (?) quadratic function**
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+ .. topic :: **Exercise : A simple (?) quadratic function**
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:class: green
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Optimize the following function, using K[0] as a starting point::
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Time your approach. Find the fastest approach. Why is BFGS not
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working well?
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- .. topic :: **Exercice : A locally flat minimum**
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+ .. topic :: **Exercise : A locally flat minimum**
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:class: green
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Consider the function `exp(-1/(.1*x**2 + y**2) `. This function admits
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The remainder of this chapter is not necessary to follow the rest of
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the intro part. But be sure to come back and finish this chapter, as
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- well as to do some more :ref: `exercices <numpy_exercises >`.
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+ well as to do some more :ref: `exercises <numpy_exercises >`.
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=====================================
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This example uses seaborn to quickly plot various factors relating wages,
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- experience and eduction .
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+ experience, and education .
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Seaborn (https://seaborn.pydata.org) is a library that combines
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visualization and statistical fits to show trends in data.
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:scale: 60
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A regression capturing the relation between one variable and another, eg
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- wage and eduction , can be plotted using :func: `seaborn.lmplot `::
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+ wage, and education , can be plotted using :func: `seaborn.lmplot `::
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>>> seaborn.lmplot(y='WAGE', x='EDUCATION', data=data) # doctest: +SKIP
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