Setting up basic Machine Learning rig - Ubuntu

For ubuntu
https://www.tensorflow.org/install/install_linux

First install python and pip

sudo apt-get install python python-pip python-dev
sudo pip install --upgrade pip virtualenv 

--- WITH A GPU ---

Install the GPU if not already done as described here:
https://www.pugetsystems.com/labs/hpc/NVIDIA-CUDA-with-Ubuntu-16-04-beta-on-a-laptop-if-you-just-cannot-wait-775/

Verify that you even have a usable gpu with (it must be one compatiable with cuda

lspci | grep -i nvidia

Install Cuda drivers

Remove prior installs (if you have a problem with it)

sudo apt-get purge nvidia-cuda* 
sudo apt-get install cuda

download the recent cuda drivers from
https://developer.nvidia.com/cuda-downloads

install the drivers

chmod 755 cuda_7.5.18_linux.run
sudo ./cuda_7.5.18_linux.run --override

Confirm setup

which nvcc 
nvcc --version
nvidia-smi

Output should be something like

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Tue_Aug_11_14:27:32_CDT_2015
Cuda compilation tools, release 7.5, V7.5.17


Sat Mar 18 14:16:58 2017       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 367.57                 Driver Version: 367.57                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 970M    Off  | 0000:01:00.0     Off |                  N/A |
| N/A   55C    P0    22W /  N/A |    586MiB /  3016MiB |      8%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|    0      1144    G   /usr/lib/xorg/Xorg                             366MiB |
|    0      1922    G   compiz                                         111MiB |
|    0      2302    G   ...bled/ExtensionDeveloperModeWarning/Defaul   107MiB |
+-----------------------------------------------------------------------------+

Install cudnn drivers
http://askubuntu.com/questions/767269/how-can-i-install-cudnn-on-ubuntu-16-04

Download the drivers
https://developer.nvidia.com/cudnn


Locate where your cuda installation is. it is /usr/lib/... and /usr/include or /urs/local/cuda/.

which nvcc 
ldconfig -p | grep cuda

Step 3: Copy the files:

cd extracted_driver/
sudo cp -P include/cudnn.h /usr/include
sudo cp -P lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
sudo chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*

Confirm setup

ldconfig -p | grep cudnn

should be something like:

libcudnn.so.5 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libcudnn.so.5
libcudnn.so (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libcudnn.so

--- INSTALL KEY TOOLS ---

Install Machine learning essentials

sudo pip install numpy
sudo pip install pandas
sudo pip install scikit-learn
sudo pip install jupyter
sudo pip install xgboost

Now you can install tensorflow with GPU as follows

sudo pip install tensorflow-gpu
sudo pip install keras    

Or without:

sudo pip install tensorflow
sudo pip install keras