I tried to use Google cloud to follow the course but found it very expensive, so I want to build a PC for deep learning but don’t know how to setup the development environment for deep learning. What kind of software, frameworks, libaries do I need to install for this course? If anyone can provide a step by step guide, that would be great.
Here are two guides I used to successfullyu setting up fastai v1.0 on my Windows 10 PC:
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[![pypi fastai version](https://img.shields.io/pypi/v/fastai.svg)](https://pypi.python.org/pypi/fastai)
[![Conda fastai version](https://img.shields.io/conda/v/fastai/fastai.svg)](https://anaconda.org/fastai/fastai)
[![fastai python compatibility](https://img.shields.io/pypi/pyversions/fastai.svg)](https://pypi.python.org/pypi/fastai)
The fastai library simplifies training fast and accurate neural nets using modern best practices. See the [fastai website](https://docs.fast.ai) to get started. The library is based on research into deep learning best practices undertaken at [fast.ai](http://www.fast.ai), and includes \"out of the box\" support for [`vision`](https://docs.fast.ai/vision.html#vision), [`text`](https://docs.fast.ai/text.html#text), [`tabular`](https://docs.fast.ai/tabular.html#tabular), and [`collab`](https://docs.fast.ai/collab.html#collab) (collaborative filtering) models. For brief examples, see the [examples](https://github.com/fastai/fastai/tree/master/examples) folder; detailed examples are provided in the full [documentation](https://docs.fast.ai/). For instance, here's how to train an MNIST model using [resnet18](https://arxiv.org/abs/1512.03385) (from the [vision example](https://github.com/fastai/fastai/blob/master/examples/vision.ipynb)):
path = untar_data(MNIST_PATH)
data = image_data_from_folder(path)
learn = cnn_learner(data, models.resnet18, metrics=accuracy)
## Note for [course.fast.ai](http://course.fast.ai) students
Jeremy also has a guide for Windows installation here:
Whilst Windows isn’t officially supported for fastai or the lessons at this stage, it does seem to be working now so those with the patience and boldness to venture into something a little new and somewhat untested, here’s instructions on getting started running on a GPU on Windows. (NB: most people using Windows on their laptops are advised to use a cloud GPU provider like Paperspace - accessing a cloud provider from Windows is well supported and tested for this course).
You must have an Nvi…