# Which csv data sets can test ability of machine learning and deep learning? [closed]

From easy to difficult , which csv data sets can test ability of learning algorithm?

I find circular curl into inside

• Your question is quite unclear. Can you elaborate a little more? – DuttaA Dec 8 '19 at 3:07
• I think MNIST might be something you're looking for. You can't download this as a csv, but you can extract into a python list for ease of use yann.lecun.com/exdb/mnist – Recessive Dec 8 '19 at 7:46
• @Recessive MNIST is not csv and its actually quite a bad dataset, accuracy is very high for almost all kinds of NNs to make any significant comment about it's effectiveness. – DuttaA Dec 8 '19 at 8:30
• Expect to use csv data set in maple instead of python – Prince Martin Dec 8 '19 at 11:06
• I find some tutorial using a recursive curl into center and a line fit through curl into center , where can find this csv data set or how to generate this difficult data to test? – Prince Martin Dec 8 '19 at 11:08

Not sure about where you can find datasets by difficulty, but I will concentrate on how you can generate your own spiral dataset.

To generate a spiral you just need to create a time vector $$t$$ (e.g., a column in excel with numbers from 0 to $$T_{max}$$) and then use the following formulas (for the next two columns):

$$x(t) = (r_0+v_rt)\cos(\omega t),\hspace{5pt} y(t) = (r_0+v_rt)\sin(\omega t),$$

where $$v_r$$ is the outward velocity of the spiral, and $$\omega$$ its angular velocity. You can choose these parameters as you like.

If you ignore the factor $$r_0+v_rt$$, you can notice that the formulas for the point $$(x,y)$$ correspond to the parametric equation of a circle. So, the factor simply changes linearly the size of this circle.