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Problem of creating knowledge graph from unstructured data is a well known machine learning problem. Not even a single org has achieved 100% accuracy for completely enriched knowledge graph . I have few findings that will help to kick-start for a person who is new in to this . Before move to findings , i will let you to walk through the problem of building knowledge graph from unstructured corpus . Lets consider this scenario . Suppose we have very small corpus : "Apple was founded by Steve jobs and current CEO is Tim Cook. Apple launched several products like Ipad, iphone , MAC etc. " Corpus may be very complex sentences also . Problem is how can we build a knowledge graph out of this unstructured corpses . If we create generic knowledge graph , then our system should be able to provide answers like "who founded Apple ?" , " What are products launched by Apple ?" etc . Few techniques to create knowledge graph : 1.) Supervised Technique : Supervised mod...

Below are the steps to setup your development environment  for Deep learning : 1.) Download and Install Anaconda from here : https://www.continuum.io/downloads 2.) Create a conda environment for data science development so that it doesn't affect the other install components .     conda create -n tensor_keras_py3.5 python=3.5 pandas scikit-learn jupyter matplotlib 3.) Activate the created environment     source activate tensor_keras_py3.5 4.) Install tensorflow inside activated env.     pip install tensorflow 5.) Install keras inside activated env.    pip install keras 6.) Install opencv inside activated env.    pip install opencv-python 7.) Install IMUTILS  pip install imutils Test your environment 1.) Type ipython in the shell  , which should open ipython console . 2.) Type import tensorflow,keras  , it should reply using tensorflow backend  Switching keras backend fro...

Here is the fastest way to get started with caffe deep learning framework with installation and basic we application demo for image classification : Installation : Here i am using caffe official ubuntu image and running it on docker . Follow the steps mentioned below : 1.) Install docker setup on your machine . Follow this link :  https://docs.docker.com/engine/installation/#time-based-release-schedule . 2.) I have build caffe ubuntu image and push to docker hub . You can pull it in to your local.    docker pull anishratnawat/caffe_deep_learning 3.)Run this command on terminal :      docker run -ti -p 5000  anishratnawat/caffe_deep_learning  bash    // it will download the image if its not downloaded before. // When downloading finishes , terminal will enter in to image bash and your terminal will change to : root@d3a683f24784:/workspace# If you install any necessary packages inside that image then you need to commit ...