Skip to content

Latest commit

 

History

History
54 lines (41 loc) · 1.54 KB

README.md

File metadata and controls

54 lines (41 loc) · 1.54 KB
Raw

Repo for MLDA Workshops

  • sponsored by MLDA@EEE
  • This repo may refer to some online materials/MOOCs and it is for educational purpose only. Pls contact Xiaofeng(fxf1996@gmail.com) if any unapproriated use found.

Python Environment (local, CPU-only) Setup Guide

Download and install Anaconda

Choose Python 3.x version: https://www.anaconda.com/download/#macos

Env Setup

1. Create Environment

Open a terminal(for Mac) / Anaconda Prompt(for Windows), type command

$ conda create -n DIP python=3.6

Then

  • for Windows, type: $ conda activate DIP
  • for mac/linux, type: $ source activate DIP

2. Install packages

Type command: $ conda install pandas numpy scikit-learn matplotlib tensorflow keras jupyterlab ipykernel

$ pip install pillow opencv-python

3. Validate your installation

Type command: $ jupyter lab to start the interactive notebook for your experiments. By default, a service will be running at http://localhost:8888/. You can access it using any browser.

Then create a notebook, run the following code:

import keras
import matplotlib
import numpy as np
import pandas as pd
import tensorflow as tf

You should see no error.

Setup on your GPU server

You are given an account to access one of our GPU stations (Tesla V100 or GTX 1080 Ti) at EEE AI Lab.

To connect to the server

$ ssh your_username@IP_ADDRESS

Install Anaconda

Run following commands:

$ cd ~
$ wget https://repo.anaconda.com/archive/Anaconda3-5.3.0-Linux-x86_64.sh
$ bash Anaconda3-5.3.0-Linux-x86_64.sh

Then make response accordingly.