Oh-my-zsh and Powerline Fonts setup for Awesome Terminal in Ubuntu 16.04

Step 1: Installing General Requirements Install Git sudo apt-get install git Install Curl sudo apt-get install curl Install pip curl --silent --show-error --retry 5 https://bootstrap.pypa.io/get-pip.py | sudo python2.7 Features: It is written in Python language, which makes it extensible and feature rich. Stable and testable code base, which works well with Python 2.6+ and Python... Continue Reading →


Installing NVIDIA Drivers and CUDA 8 Toolkit on Ubuntu 16.04

Step 1: Update and upgrade your system apt-get update && apt-get upgrade -y Step 2: Install Linux Headers (for installing aptitude "apt install aptitude") aptitude -r install linux-headers-$(uname -r) Step 3: apt-get purge nvidia-* Step 4: add-apt-repository ppa:graphics-drivers/ppa Step 5: apt-get update Step 6: apt-get install nvidia-375 Step 7: Create a file and paste the... Continue Reading →

Installing TensorFlow GPU version on Ubuntu 16.04

NVIDIA requirements to run TensorFlow with GPU support CUDA┬« Toolkit 8.0. For details, see NVIDIA's documentation. Ensure that you append the relevant Cuda pathnames to the LD_LIBRARY_PATH environment variable as described in the NVIDIA documentation. The NVIDIA drivers associated with CUDA Toolkit 8.0. cuDNN v5.1. For details, see NVIDIA's documentation. Ensure that you create the... Continue Reading →

Setup DIGITS (Deep Learning GPU Training System) on Ubuntu 16.04

DIGITS (the Deep Learning GPU Training System) is a webapp for training deep learning models. The currently supported frameworks are: Caffe, Torch, and Tensorflow. Since DIGITS itself is a pure Python project, installation is usually pretty trivial regardless of the platform. The difficulty comes from installing all the required dependencies for Caffe and/or Torch7 and... Continue Reading →

Setup char-rnn and torch-rnn for character level language model in Torch

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch Requirements This code is written in Lua and requires Torch. So Follow the tutorial provided in my previous blog post for installing Torch. https://dwijaybane.wordpress.com/2017/07/22/installing-torch-7-deep-learning-on-ubuntu-16-04/ Lua Pre-requisite # Install most things using luarocks luarocks install torch luarocks install nn luarocks install optim luarocks... Continue Reading →

Installing Overfeat: CNN based feature extractor and classifier on Ubuntu 16.04

Step 1: Download the archive from the link below http://cilvr.cs.nyu.edu/lib/exe/fetch.php?media=overfeat:overfeat-v04-2.tgz Step 2: Extract and prepare tar -xvzf overfeat-v04-2.tgz cd overfeat python download_weights.py git pull Step 3: A simple test of the pre-compiled binaries can be done with following command #for 64bit OS ./bin/linux_64/overfeat -n 3 samples/bee.jpg Step 3: Overfeat can run without BLAS, however it... Continue Reading →

Setup Theano and Keras with CUDA support on Ubuntu 16.04

Make sure you have installed Nvidia drivers and cuda toolkit on your system. Also follow caffe setup for preliminary setup of libraries. Step 1: Install Dependencies sudo apt-get install python-numpy python-scipy python-dev python-pip python-nose g++ libopenblas-dev liblapack-dev gfortran git Step 2: Now Install Theano sudo pip install Theano Step 3: Work around for a glibc... Continue Reading →

Installing Torch 7 deep learning on Ubuntu 16.04

Make sure you have followed caffe setup if not atleast install Prerequisite packages from that post. Step 1: install general dependencies sudo apt-get install --no-install-recommends git software-properties-common Step 2: gedit ~/.bashrc (append following lines) and restart terminal (source ~/.bashrc) export TORCH_ROOT=~/torch Step 3: Download Torch repo in that root location git clone https://github.com/torch/distro.git $TORCH_ROOT --recursive... Continue Reading →

FFMPEG with NVIDIA Acceleration on Ubuntu 16.04 (NVENC SDK)

The Video Codec SDK includes a complete set of high-performance tools, samples and documentation for hardware accelerated video encode and decode on Windows and Linux. The SDK consists of two hardware acceleration interfaces: NVENCODE API for video encode acceleration NVDECODE API for video decode acceleration (formerly called NVCUVID API) NVIDIA GPUs contain one or more... Continue Reading →

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