-
Notifications
You must be signed in to change notification settings - Fork 12
/
Setup Instructions.txt
42 lines (30 loc) · 1.76 KB
/
Setup Instructions.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Basic Setup for Machine Learning
---------------------------------
1. Make an virtual environment (this is a safe practice)
For Windows users, use Anaconda
Ubuntu users can also use Anaconda or stick with pip
Note: Ubuntu is recommended over Windows
Anaconda virtualenv: https://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/20/conda/
Ubuntu virtualenv: https://youtu.be/NTiuK1kVprs
For steps 2 and 3 follow the commands given in the end sequentially.
2. Install Python on your machine (I'd recommend Python 3.5+)
3. In this virtualenv, install the following packages
numpy, scipy, matplotlib, sklearn, pandas, seaborn
Other useful packages are Pytorch (torch), TensorFlow with keras [OPTIONAL]
Ubuntu commands:
In your virtualenv (i.e after source ml_env/bin/activate where ml_env is what I've named my virtualenv),
sudo apt-get update
sudo apt-get install python3.6 (for python 3.6.1) or sudo apt-get install python3 (for python3.5)
sudo apt-get install python3-pip python3-dev
sudo pip3 install numpy scipy matplotlib
sudo apt-get install python3-pandas
pip3 install jupyter
pip install -U scikit-learn
Anaconda User Commands
Note sometimes installing from conda install will have connectivity error with continuum.io. This is fairly common and just repeating a few times solves this problem. Dont be surprised if you have to do this for almost every command, this is due to IITB proxy settings.
In your Anaconda Prompt, after activating your virtualenv,
conda install numpy scipy
conda install -c conda-forge matplotlib
pip install pandas scikit-learn jupyter
conda install -c anaconda seaborn
Link for Conda on windows: http://www.mikelanzetta.com/deep-learning-on-windows-redux.html