Try Deep Learning in Python now with a fully pre-configured VM

Try #DeepLearning in #Python now with a fully pre-configured VM

  • Try Deep Learning in Python now with a fully pre-configured VMI love to write about face recognition, image recognition and all the other cool things you can build with machine learning.
  • If you aren’t a long-time Linux user, it can be really hard to figure out how to get a system fully configured with all the required machine learning libraries and tools like TensorFlow, Theano, Keras, OpenCV, and dlib.
  • To make it simple for anyone to play around with machine learning, I’ve put together a simple virtual machine image that you can download and run without any complicated installation steps.The virtual machine image has Ubuntu Linux Desktop 16.04 LTS 64-bit pre-installed with the following machine learning tools:Python 3.5OpenCV 3.2 with Python 3 bindingsdlib 19.4 with Python 3 bindingsTensorFlow 1.0 for Python 3Keras 2.0 for Python 3Theanoface_recognition for Python 3 (for playing around with face recognition)PyCharm Community Edition already set up and ready to go for all these librariesConvenient code examples ready to run, right on the desktop!Even the webcam is preconfigured to work inside the Linux VM for OpenCV / face_recognition examples (as long as you set up your webcam to be accessible in the VMware settings).
  • So don’t the VirtualBox version unless you don’t have any other choice.You need VMware to run this virtual machine image.
  • Right-click on the code window and choose “Run” to run the current file in PyCharm.If you configure your webcam in VMware settings, you can access your webcam from inside the Linux virtual machine!

I love to write about face recognition, image recognition and all the other cool things you can build with machine learning. Whenever possible, I try to include code examples or even write libraries…
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Elon Musk and Google Want You to Make Their Artificial Intelligence Smarter

  • Google’s DeepMind , the AI system that famously defeated the world champion of the board game Go earlier this year, and OpenAI , an AI collaboration from Elon Musk and others, are making their software platforms available to researchers, developers, and anyone else who wants to use them.
  • Elon Musk and Google Want You to Make Their Artificial Intelligence Smarter
  • Open sourcing an AI system allows it to access troves of new learning data, so the more people who use it, the stronger it becomes.
  • Developers could conceivably use these platforms to make the AI in their own games and apps smarter.
  • The two platforms both use deep learning, a form of machine learning that allows AI systems to grow smarter.

Musk’s OpenAI and Google’s DeepMind are opening their platforms to the public.
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​How AI could help save the humble sea cow

How AI could help save the humble sea cow

  • Discuss: How AI could help save the humble sea cow
  • The same AI approach could be used to track other threatened populations, ensuring that sea cows will have some playmates.
  • Google puts repeatedly dangerous websites on notice
  • Using the open-source TensorFlow software, researcher Amanda Hodgson of Murdoch University and her team built a detector to find sea cows in the photos, Gordon said.
  • Google’s neural network software is being used to scan thousands of photos to detect the cute mammals threatened by extinction.

Google’s neural network software is being used to scan thousands of photos to detect the cute mammals threatened by extinction.
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A Development Methodology for Deep Learning – Medium

A Development Methodology for #DeepLearning.  #BigData #MachineLearning #DataScience #AI

  • The machine learning convention has been to create a training set, a validation set and a test set.
  • Although Deep Learning is built from software it is a different kind of software and a different kind of methodology is needed.
  • The observations that differs from conventional machine learning is that Deep Learning has more flexibility in that a developer has the additional options of employing either a bigger model or using more data.
  • The methodology addresses the necessary interplay of the need for more training data and the exploration of alternative Deep Learning patterns that drive the discovery of an effective architecture.
  • Deep Learning differs most from traditional software development in that a substantial portion of the process involves the machine learning how to achieve objectives.

The practice of software development has created development methodologies such agile development and lean methodology to tackle the…
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