Will do. (I remember now, that was in the original comments and I forgot to
do that.)


On 26 May 2013 18:37, Mathieu Blondel <math...@mblondel.org> wrote:

> I wouldn't use isotonic regression to illustrate regression, since it has
> a quite different purpose.
>
> You could use the polynomial curve fitting example
>
> http://scikit-learn.org/stable/auto_examples/linear_model/plot_polynomial_interpolation.html
>
> This example also illustrates that too complex models tend to overfit and
> too simplistic models will underfit.
>
> Mathieu
>
> On Sun, May 26, 2013 at 12:33 PM, Robert Layton <robertlay...@gmail.com>wrote:
>
>> I've updated the slides for my talk at pycon AU and put them on my Google
>> Drive:
>> https://docs.google.com/file/d/0B8FUzd86yYa1VnYtZ1ZHVV9ieUk/edit?usp=sharing
>>
>> If anyone has any comments, I'm happy to take them.
>>
>> Thanks!
>>
>> - Robert
>>
>>
>> On 3 May 2013 13:18, Robert Layton <robertlay...@gmail.com> wrote:
>>
>>> I sent around an early draft of the slides a few weeks ago, and will do
>>> another edit before sending it around again. Thanks for the interest and
>>> kudos!
>>>
>>>
>>>  On 2 May 2013 23:27, Jaques Grobler <jaquesgrob...@gmail.com> wrote:
>>>
>>>>  Big congrats Robert! Hope we can see the slides! [?]
>>>>
>>>>
>>>> 2013/4/29 Lee Zamparo <zamp...@gmail.com>
>>>>
>>>>> Congrats Robert!
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> On Sun, Apr 28, 2013 at 7:56 AM, Robert Layton <robertlay...@gmail.com
>>>>> > wrote:
>>>>>
>>>>>> I just received some good news. My talk "scikit-learn, machine
>>>>>> learning and cybercrime attribution" has been accepted!
>>>>>>
>>>>>> I'll be presenting between the 5th and 7th of July. For those that
>>>>>> missed the previous emails, my presentation will be sklearn-centric, with
>>>>>> an light introduction to machine learning, and then a brief overview of 
>>>>>> my
>>>>>> research in cybercrime attribution.
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Robert
>>>>>>
>>>>>> --
>>>>>>
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>>>>>>
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>>
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