karlmutch

from tensorflow.python.client import device_lib

def get_available_gpus():
    local_device_protos = device_lib.list_local_devices()
    return [x.name for x in local_device_protos if x.device_type == 'GPU']

get_available_gpus()

karlmutch

 wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
 dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
 apt-get update
 apt-get install cuda-nvrtc-8-0 cuda-nvgraph-8-0 cuda-cusolver-8-0 cuda-cublas-8-0 cuda-cufft-8-0 cuda-curand-8-0 cuda-cusparse-8-0 cuda-npp-8-0 cuda-cudart-8-0 cuda-drivers
 nvidia-smi
 sudo rmmod nvidia_drm
 sudo rmmod nvidia_modeset
 sudo rmmod nvidia_uvm
 sudo rmmod nvidia
 nvidia-smi

karlmutch

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda

karlmutch

##################################################################################################
# experiments service
##################################################################################################
apiVersion: v1
kind: Service
metadata:
  labels:
    service: ambassador
  name: ambassador
  annotations:

karlmutch

https://www.dataquest.io/blog/basic-statistics-with-python-descriptive-statistics/

https://blogs.oracle.com/ai/types-of-machine-learning-and-top-10-algorithms-everyone-should-know

https://www.kdnuggets.com/2018/05/5-reasons-logistic-regression-first-data-scientist.html
https://www.kdnuggets.com/2018/02/logistic-regression-concise-technical-overview.html

https://towardsdatascience.com/types-of-machine-learning-algorithms-you-should-know-953a08248861

https://machinelearningmastery.com/a-gentle-introduction-to-the-central-limit-theorem-for-machine-learning/

karlmutch

# Add this snippet to the top of your playbook. 
# It will install python2 if missing (but checks first so no expensive repeated apt updates)
# gwillem@gmail.com

- hosts: all
  gather_facts: False
  
  tasks:
  - name: install python 2
    raw: test -e /usr/bin/python || (apt -y update && apt install -y python-minimal)

karlmutch

Updated 4/11/2018

Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install CUDA
• Install cuDNN

Table of contents generated with markdown-toc

karlmutch

See also, http://libraryofalexandria.io/cgo/

Using Go cgo

cgo has a lot of trap.
but Not "C" pkg also directory in $GOROOT/src. IDE's(vim) Goto command not works.

So, Here collect materials.

karlmutch

// Found at https://play.golang.org/p/pQn_doizkn_L

package main

import (
	"fmt"
	"reflect"
)

var strs = make(map[reflect.Type]map[int]string)

karlmutch

sudo vi /etc/sysctl.conf 

# Add the following to sysctl.conf:

# Decrease TIME_WAIT seconds
net.ipv4.tcp_fin_timeout = 30

# Recycle and Reuse TIME_WAIT sockets faster
net.ipv4.tcp_tw_recycle = 1