# Deep Learning (with PyTorch) [](https://mybinder.org/v2/gh/Atcold/pytorch-Deep-Learning/master)
This notebook repository now has a [companion website](https://atcold.github.io/pytorch-Deep-Learning/), where all the course material can be found in video and textual format.
这份`README.md`的中文版本及网站可以在[这里](https://github.com/Atcold/pytorch-Deep-Learning/blob/master/docs/zh/README-ZH.md)找到.
# Getting started
To be able to follow the exercises, you are going to need a laptop with Miniconda (a minimal version of Anaconda) and several Python packages installed.
The following instruction would work as is for Mac or Ubuntu Linux users, Windows users would need to install and work in the [Git BASH](https://gitforwindows.org/) terminal.
## Download and install Miniconda
Please go to the [Anaconda website](https://conda.io/miniconda.html).
Download and install *the latest* Miniconda version for *Python* 3.7 for your operating system.
```bash
wget <http:// link to miniconda>
sh <miniconda*.sh>
```
## Check-out the git repository with the exercise
Once Miniconda is ready, checkout the course repository and proceed with setting up the environment:
```bash
git clone https://github.com/Atcold/pytorch-Deep-Learning
```
## Create isolated Miniconda environment
Change directory (`cd`) into the course folder, then type:
```bash
# cd pytorch-Deep-Learning
conda env create -f environment.yml
source activate pDL
```
## Start Jupyter Notebook or JupyterLab
Start from terminal as usual:
```bash
jupyter lab
```
Or, for the classic interface:
```bash
jupyter notebook
```
## Notebooks visualisation
*Jupyter Notebooks* are used throughout these lectures for interactive data exploration and visualisation.
We use dark styles for both *GitHub* and *Jupyter Notebook*.
You should try to do the same, or they will look ugly.
JupyterLab has a built-in selectable dark theme, so you only need to install something if you want to use the classic notebook interface.
To see the content appropriately in the classic interface install the following:
- [*Jupyter Notebook* dark theme](https://userstyles.org/styles/153443/jupyter-notebook-dark);
- [*GitHub* dark theme](https://userstyles.org/styles/37035/github-dark) and comment out the `invert #fff to #181818` code block.
PyTorch技术笔记教程
需积分: 5 53 浏览量
2023-12-09
09:28:26
上传
评论
收藏 32.14MB ZIP 举报
PyTorch技术笔记教程 （187个子文件） 
various_input.gif 240KB feature_binding.gif 237KB shift_invariance.gif 182KB
.gitignore 225B .gitmodules 94B
withmacros.html 108B default.html 35B 404.html 19B 08-seq_classification.ipynb 23KB 12-regularization.ipynb 19KB 01-tensor_tutorial.ipynb 18KB 06-convnet.ipynb 14KB 14-truck_backer-upper.ipynb 13KB 05-regression.ipynb 9KB 07-listening_to_kernels.ipynb 9KB 00-logic_neuron_programming.ipynb 9KB 11-VAE.ipynb 8KB b-custom_grads.ipynb 8KB 10-autoencoder.ipynb 7KB 04-spiral_classification.ipynb 7KB 09-echo_data.ipynb 7KB 03-autograd_tutorial.ipynb 7KB 02-space_stretching.ipynb 7KB 13-bayesian_nn.ipynb 4KB a-projections.ipynb 4KB
Figure 1 Fully Connected Network.jpg 223KB example.jpg 214KB Figure1.jpg 55KB 03-1.md 18KB 02-3.md 17KB 05-2.md 17KB 02-1.md 17KB 03-2.md 12KB 04-1.md 12KB 03-3.md 11KB 02-2.md 10KB 01-1.md 10KB 05-3.md 10KB 05-1.md 10KB 01-3.md 8KB 01-2.md 8KB index.md 8KB 01-2.md 8KB 01-3.md 7KB 01-1.md 6KB index.md 5KB about.md 4KB README.md 2KB README.md 2KB README-ZH.md 2KB 01.md 1KB 05.md 1KB 02.md 1KB 03.md 1KB 02.md 1KB 01.md 1KB 04.md 403B 02-2.md 375B 02-1.md 345B LICENSE.md 281B 02-3.md 251B about.md 170B
04 - RNN.pdf 2.28MB 05 - Generative models.pdf 1.96MB 06 - How to present.pdf 1.4MB 02 - CNN.pdf 1.34MB 09 - Controller learning.pdf 1.16MB 01 - Spiral classification.pdf 911KB 07 - Regularisation.pdf 623KB 08 - Bayesian NN.pdf 611KB 00 - Logic neurons.pdf 542KB 03 - Salsa.pdf 241KB 00 - ML taxonomy.pdf 168KB
cnn_features.png 2.33MB Gallant_and_Van_Essen.png 1.19MB fig4.png 876KB 5_2_vgg.png 829KB spectrogram.png 724KB matrix_multiplication_with_nonlinearity_s=1_lab1.png 555KB Visual1.png 525KB 5_2_comparison.png 489KB momentum.png 487KB 6-nn-confidence.png 448KB pre-inference4layers.png 441KB initial_scatter_lab1.png 437KB sgd-vs-momentum.png 432KB noisy-spiral.png 415KB momentum-beta.png 415KB detailed_convNet.png 401KB fig5.png 338KB 5_2_norm_operations.png 335KB fig7.png 324KB Figure 5 Information Representations Moving up the Hierachy.png 314KB audioSignal.png 305KB fig6.png 288KB Figure3.png 281KB Visual3.png 280KB clean-spiral.png 267KB matrix_multiplication_lab1.png 256KB Network.png 254KB共 187 条
- 1
- 2
资源评论
