All entries for December 2019

teaching schedule, now ready

Follow-up to Machine Learning – a hands–on course from Rudo's blog

Dear all,

the schedule of the course has now become clearer: we continue to teach every Monday 0930-1230 in room E4.28 (except for one day in January and one day in February) for 10 weeks overall. For the 1st 5 weeks (with 4 more weeks to come), I will actually "teach", i.e. with prepared lectures for 2 hours 0930-1130, while Djenabou will be available for 1 hr more 1130-1230 to help you with the exercises. Then in the last 5 weeks, Djenabou will be available 0930-1230 to help with your project work (she won't do it for you, but might be able to help with technical problems).

A full schedule should be available soon.

See you next Monday!

-Rudo

Rudo Roemer : 12 Dec 2019 15:53 |  Tags: Fastai Keras Machine-Learning Tensorflow |  Comments (0) |  Close comments |  Report a problem

Thoughts on the 1st lecture session

Writing about web page /rroemer/entry/installing_your_own/

Writing about an entry you don't have permission to view

Dear all,

[1] today in the lecture, we saw that it was not entirely simple to install your own ML machine with Tensorflow/Keras and FastAI. I have now made a blog entry on how to do this. You can find it here.

[2] In addition, when running the FastAI code, we saw that it might take a long time even for just the pets categorization. I just ran the pets notebook (please download a new version) and have made the pets-stage-1 and pets-stage-1-50 trained models available on the download area. You need to move these models into where FastAI keeps them which in my set-up is

/home/phsht/.fastai/data/oxford-iiit-pet/images/models

Just copy the twp .pth files there and you should be able to run the pets code after the

learn.load('pets-stage-1')

fastai commands in the notebook.

[3] When you "play" with the notebook called "FastAI-lesson2-download.ipynb", note that the file data.zip contains the cats/teddys/wolves that I managed to download and use for the exercise.

[4] Some of you argued that your own machines may not be able to do meaningful ML as you do not have a GPU. Have a look at what the FastAI guys have collected in terms of possible free GPU instances, i.e. Using a GPU. I have not yet used any of these services, but would be keen to learn from your experiences!

OK, keep checking this blog for up-to-date information before we meet again next week.

Rudo Roemer : 09 Dec 2019 16:29 |  Tags: Fastai Keras Machine-Learning Tensorflow |  Comments (2) |  Close comments |  Report a problem

Things to do before the 1st lectures

Follow-up to Machine Learning – a hands–on course from Rudo's blog

Dear all,

[1] some of you will have registered for the short Machine Learning (ML) course that we are planning to give, starting next week. ML is best "learned" by doing it, so we are planning to use the computer room E4.28 for exercises during all the lectures. But we think you might also find it more useful if you were to bring your laptops along and install+run the ML codes there.

[2] We are expecting to run all the ML on a Ubuntu installation (Francois Chollet, one of the key people in the field, says "it’s possible to use Windows, too, but I don’t recommend it"). Other Linux installations should also work. If you only have Windows, Rudo recommends installing

VirtualBox, https://www.virtualbox.org/

with a Ubuntu 19.10 installation (http://releases.ubuntu.com/19.10/).

[3] During the course, we intend to offer you downloadable ML source codes via Rudo's blog at

https://blogs.warwick.ac.uk/rroemer/entry/machine_learning_a/

where you can also see a copy of this email. The direct download link is in the first entry of the blog and given here as well, i.e.

https://cloud.csc.warwick.ac.uk/index.php/s/JomfpoMj87X3Jbk

[4] We want to share literature on ML with you using Mendeley, i.e. https://www.mendeley.com/. Although the Mendeley Desktop might be convenient to install (we have it on our machines), the online interface could be ok for the course. But in order to "share" PDFs with you, you need to have a (free) Mendeley account. Please create one.

[5] Last, we, Djena and Rudo, are both new to ML, so this will be a course where we will all explore ML together! We hope you'll enjoy it.

- Rudo and Djena

Rudo Roemer : 06 Dec 2019 09:13 |  Tags: Fastai Keras Machine-Learning Tensorflow |  Comments (0) |  Close comments |  Report a problem

Machine Learning – a hands–on course

Dear all,

for this course, you should be able to find all course material for download at

https://cloud.csc.warwick.ac.uk/index.php/s/JomfpoMj87X3Jbk

Please let me know in case this does not work!

-Rudo

Rudo Roemer : 05 Dec 2019 16:29 |  Tags: Fastai Keras Machine-Learning Tensorflow |  Comments (4) |  Close comments |  Report a problem