Hi Forum Admins,
I noticed that the access to the “Advanced Discussion” sub-forum is still private even after the launch of the course to everyone. Is this intended?
https://forums.fast.ai/c/part1-v3/part1-v3-adv
Thanks.
I found your site and spend a whole day ,It seems a great work!
But I don’t know how to start. How to set up ? The site and website seems very very messy for me.
I read https://course.fast.ai/ and searched forum and watched video.
But the video is not clear for me. How to start?
It is very hard for beginners although I am familiar with deep learning and tools (caffe,TF, pytorch) for several years. Your course seems hard to follow.
You can start with Google Cloab. If you’re not sure how to work with Google Cloab. Do let me know.
Thanks
Thank you .
I can run fast.ai lessons on Google Cloab
@jeremy are we also getting a new machine learning course?
Are there special installation steps for running the fastai code in a windows machine?
I am trying to run the untar_data() function on kaggle kernel, i am getting error:
ERROR NOTE: ConnectionError: HTTPSConnectionPool(host=‘s3.amazonaws.com’, port=443): Max retries exceeded with url: /fast-ai-imageclas/oxford-iiit-pet.tgz (Caused by NewConnectionError(’<urllib3.connection.VerifiedHTTPSConnection object at 0x7f029e361630>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution’,))
Can anyone let know why this happening?
Hey @jeremy, I just created my own image classifier after seeing lesson 2 of the deep learning course. It was a classifier to distinguish between guitars and violins. I was so happy to get a 98% accuracy on my classifier. Thanks for helping me create this!!
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Pytorch 1.0 is officially released but I think if you search you will find others. Windows is running slower than Linux right now - threads on that too
.
I am trying to get ImageDataBunch.from_folder to work and I keep getting this warning:
UserWarning: There seems to be something wrong with your dataset, can't access these elements in self.train_ds: 10
I am calling it this way:
mini_bs = 16
jet_data = ImageDataBunch.from_folder(jet_path, ds_tfms=get_transforms(),
valid_pct=0.25, size=224, bs=mini_bs)
Where jet_path is the directory with my data. Within jet_path I do not have a “train” or “valid” folder and instead just have jet_path/class1 containing all my images of class1, and jet_path/class2 containing all my images of class 2. I tried setting up the directory as jet_path/train/class1 and jet_path/train/class2 but that did not seem to help. Does anyone have any idea what I might be doing wrong?
I am excited about this class. I was trying to create a sample application with my model.
I can just train it from a jupyter notebook and save the model. According to the documentation, I can use predict on vision.learner. My question is how would I do this for a production system, where my images come from a video.
I could use opencv or something like it to pull out images from the video, then load each image and call predict on it. (I used opencv to pull out images for my training set).
I that the best approach, or is there a better way of doing this? Also what would you recommend as a server? AWS?
The URLs.PETS you are trying to untar is not really available in the Kaggle environment/Docker. The URL is for data to be downloaded from Amazon servers (where the dataset has been hosted by fastai devs) which won’t be possible in Kaggle kernels. Otherwise, if you try untar_data() on a kaggle dataset itself, it works.
You probably will have to use OpenCV to pull out images and feed to the model in production as well (I did the same when I was playing around with videos).
For server side, I prefer GCP, but if you are familiar with AWS then you may try it as well.
Hi there. Just started the Fast.ai course. Hardest part so far has been navigating these forums 
Anyhow trying to post every day so hopefully get better at this. Course has been great so far and Jeremy’s teaching style is relaxed and efficient.
Hi all,
Nice to e-meet you. These forum is definitely not trivial. Up to this moment, I am not sure how to write a new message.
I would like to discuss installation for working with Google Cloud Datalab. I was able to run
pip install fastai
from fastai import *
from fastai.vision import *
The last command, fires an error:
ImportErrorTraceback (most recent call last) <ipython-input-14-c0e76450f370> in <module>() ----> 1 from fastai.vision import * ImportError: No module named vision
Please advice.
Thanks,
Eila
TOPBOTS, run by Mariya Yao, offers weekly summaries of the latest AI papers organized by topic. Looks useful for keeping current!
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you should probably post that question in the “fastai users” subsection of the forum. It’s for everything related to the library itself 
Note that I would help you with the answer if I could, but I have no idea what’s going on.
Hello everyone !
Does anyone have a clue where it would be possible to stay in SF if I was to come for PART2 of the course ? I’ve looked at Airbnbs but they are either overpriced, or too far away from the Data Institute…
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how to create my own validation and test set and use them in an image classifier?
I’m aware, from doing Part1 in person, that some used student accommodation to say in SF. For example, http://www.usastudentresidences.com offer both private and shared rooms and their 2018 rates, when I enquired in early October 2018, were;
USA Student Residences
711 Post St
2018 rates
Room Type Monthly
Private Room/ Private Bath $1,975
Private Room/ Shared Bath $1,700
Shared Room/ Private Bath $1,275
Shared Room/ Shared Bath $1,000
When I enquired, the private rooms with private bath were all booked up, so I think it’s best to plan well ahead.
Others I knew who stayed in SF either lived there, or knew someone they could stay with. I did search for a good value accommodation in SF, but I found that it can take just as long, or longer, to take public transport across the city as it does to arrive into Embarcadero from the East Bay.
I found that AirBnb prices dropped dramatically if I travelled 30-55mins by BART. I found the BART system brilliant, and a very easy way to get to Howard St. when you get off at Embarcadero. I stayed in various AirBnbs (e.g. Pittsburgh/BayPoint (c.53mins direct to/from Embarcadero), South Hayward (c.36mins away direct) and Lafayette (c.31mins direct trains). Of these, Lafayette was the most pleasant area by far, but also the most expensive of the three. I can give you more info if you want to DM me, although I’m aware there are many places to stay, and my experience is just one small slice of what’s available.
I can understand why you want to stay in SF, and I hope you find something good.
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