diegopacheco

sudo apt-get install autoconf automake libtool curl make g++ unzip -y
git clone https://github.com/google/protobuf.git
cd protobuf
git submodule update --init --recursive
./autogen.sh
make
make check
sudo make install
sudo ldconfig

datjko

datasets

• 7* https://en.wikipedia.org/wiki/List_of_datasets_for_machine_learning_research

• 4* https://github.com/deepmind/lab

• 7* http://unrealcv.org/

• 6* http://sceneparsing.csail.mit.edu/

• https://sites.google.com/view/pasd/home

arundasan91

Freshly brewed !

With the availability of huge amount of data for research and powerfull machines to run your code on, Machine Learning and Neural Networks is gaining their foot again and impacting us more than ever in our everyday lives. With huge players like Google opensourcing part of their Machine Learning systems like the TensorFlow software library for numerical computation, there are many options for someone interested in starting off with Machine Learning/Neural Nets to choose from. Caffe, a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and its contributors, comes to the play with a fresh cup of coffee.

Installation Instructions (Ubuntu 14 Trusty)

The following section is divided in to two parts. Caffe's documentation suggest

eerwitt

# Typical setup to include TensorFlow.
import tensorflow as tf

# Make a queue of file names including all the JPEG images files in the relative
# image directory.
filename_queue = tf.train.string_input_producer(
    tf.train.match_filenames_once("./images/*.jpg"))

# Read an entire image file which is required since they're JPEGs, if the images
# are too large they could be split in advance to smaller files or use the Fixed

alefteris

#!/usr/bin/env xdg-open

[Desktop Entry]
Version=1.0
Type=Application
Terminal=false
StartupNotify=true
Name=Smartgit
Exec=env SMARTGIT_JAVA_HOME=/opt/apps/jre7/ /opt/apps/smartgit/bin/smartgit.sh
Icon=/opt/apps/smartgit/bin/smartgit-64.png