Размер видео: 1280 X 720853 X 480640 X 360
Показать панель управления
Автовоспроизведение
Автоповтор
1:13:30 Moving window function explanation1:20:50 Moving window function code1:50:25 Self-correlation explanation1:57:45 Self-correlation code2:05:55 Munging and stationarity explanation2:15:00 Forecasting explanation2:24:30 AR+MA processes code2:47:55 Clustering & classification explanation2:53:05 Clustering & classification code3:07:27 Other explanations: Vector autoregression, Kalman filter, hidden Markov models, recurrent neural networks
great talk Aileen! thank you for sharing your knowledge! you are an excellent teacher, totally enjoyed your presentation
52:00 if you are already familiar with pandas and pandas date/time functionality.
OMG , the best Video about Time Series
Thanks a lot...gives sense of direction to understand the concept. But for intermediate level.
Thank you so much for this, it was really informative.
This is the most epic video of all time
Thank you for the talk, really appreciated. Where to find the code used ?
59:06no that's because you wrote `converted[1:10]` instead of `[0:10]` (or `[:10]`)
+PyCon 2017 please update the notebook to github. Old one was not organized and I am unable to follow with the video.
I'm not sure about the origin of this repo, but checkout github.com/ikding/pycon_time_series .
What is the difference between the 2016 talk and this one?
Thanks a lot, very nice job!
ps.: for me, best explanation of acf and pacf - and i ve seen a lot of videos and papers about this topic so far!!
12.5 - TimeSeries Begining
like
she did such a bad job of explaining when to use rolling functions over extending functions! confused me on what i knew already :/
Make a better one yourself then
When I was doing PhD in physics ... How old is this chick.... Good vedio though..
She was a lawyer, before she dwelled into physics. May be that's why she's presenting in SciPy, Pycon annual conventions. Not sure about PhD though.
The presenter is really weird
1:13:30 Moving window function explanation
1:20:50 Moving window function code
1:50:25 Self-correlation explanation
1:57:45 Self-correlation code
2:05:55 Munging and stationarity explanation
2:15:00 Forecasting explanation
2:24:30 AR+MA processes code
2:47:55 Clustering & classification explanation
2:53:05 Clustering & classification code
3:07:27 Other explanations: Vector autoregression, Kalman filter, hidden Markov models, recurrent neural networks
great talk Aileen! thank you for sharing your knowledge! you are an excellent teacher, totally enjoyed your presentation
52:00 if you are already familiar with pandas and pandas date/time functionality.
OMG , the best Video about Time Series
Thanks a lot...gives sense of direction to understand the concept. But for intermediate level.
Thank you so much for this, it was really informative.
This is the most epic video of all time
Thank you for the talk, really appreciated. Where to find the code used ?
59:06
no that's because you wrote `converted[1:10]` instead of `[0:10]` (or `[:10]`)
+PyCon 2017 please update the notebook to github. Old one was not organized and I am unable to follow with the video.
I'm not sure about the origin of this repo, but checkout github.com/ikding/pycon_time_series .
What is the difference between the 2016 talk and this one?
Thanks a lot, very nice job!
ps.: for me, best explanation of acf and pacf - and i ve seen a lot of videos and papers about this topic so far!!
12.5 - TimeSeries Begining
like
she did such a bad job of explaining when to use rolling functions over extending functions! confused me on what i knew already :/
Make a better one yourself then
When I was doing PhD in physics ... How old is this chick.... Good vedio though..
She was a lawyer, before she dwelled into physics. May be that's why she's presenting in SciPy, Pycon annual conventions. Not sure about PhD though.
The presenter is really weird