Design Patterns for Deep Learning Architectures

Design Patterns for #DeepLearning Architectures:  #BigData #DataScience #MachineLearning

  • We purposely use “pattern language” to reflect that the field of Deep Learning is a nascent, but rapidly evolving, field that is not as mature as other topics in computer science.
  • Each pattern describes a problem and offers alternative solutions.
  • You can find more details on this book at: A Pattern Language for Deep Learning .
  • Pattern Languages are languages derived from entities called patterns that when combined form solutions to complex problems.
  • Or you can check for updates at Design Patterns for Deep Learning

Deep Learning can be described as a new machine learning toolkit that has a high likelihood to lead to more advanced forms of artificial intelligence. The evidence for this is in the sheer number of breakthroughs that had occurred since the beginning of this decade. There is a new found optimism in the air and we are now again in a new AI spring. Unfortunately, the current state of deep learning appears to many ways to be akin to alchemy. Everybody seems to have their own black-magic methods of designing architectures. The field thus needs to move forward and strive towards chemistry, or perhaps even a periodic table for deep learning. Although deep learning is still in its early infancy of development, this book strives towards some kind of unification of the ideas in deep learning. It leverages a method of description called pattern languages.
Continue reading “Design Patterns for Deep Learning Architectures”

Geoffrey Hinton talks about Deep Learning, Google and Everything

Learn top @google #AI thought leader, Geoffrey Hinton's perspective on #Deeplearning:

  • KDnuggets Home > News > 2014 > Dec > Opinions, Interviews, Reports > Geoffrey Hinton talks about Deep Learning, Google and Everything ( 14:n32 )
  • Dr. Hinton made a couple of points about Deep Learning and how our brain works on his AMA.
  • Its the first time I’ve believed that deep learning would be able to do real reasoning in the not too distant future.
  • I think the long-term future (of machine learning) is quite likely to be something that most researchers currently regard as utterly ridiculous and would reject as a NIPS paper.
  • Dr. Hinton started a course “Neural Networks for machine learning” on Coursera, which introduces artificial neural networks and its application.


A review of Dr. Geoffrey Hinton’s Ask Me Anything on Reddit. He talked about his current research and his thought on some deep learning issues.

Continue reading “Geoffrey Hinton talks about Deep Learning, Google and Everything”

Holistic Security Centered on Identity

On Aug. 30, join us in learning how to keep your #apps and #data safe with #machinelearning.

  • Each of our organizations exist in a cloud-first, mobile-first world where data is accessed, used, shared, and processed in the cloud and SaaS apps – places where traditional approaches to security simply cannot provide adequate protection.
  • In the presentation we’ll examine how to provide your organization with the critical balance of security while keeping your employees productive.
  • Join speaker Adam Baron for this webinar, August 30 th 10am PDT, and learn how the Enterprise Mobility + Security solution can restrict data access to your workforce while taking action to stop intrusions, as well as how to keep apps and data secure with machine learning that recognizes user behavior and actively identifies breaches.
  • The security shortfall leads to compromised customer records, stolen data, and millions lost in breaches – just to name a few.
  • Holistic Security Centered on Identity

Read the full article, click here.


@MSCloud: “On Aug. 30, join us in learning how to keep your #apps and #data safe with #machinelearning.”


Each of our organizations exist in a cloud-first, mobile-first world where data is accessed, used, shared, and processed in the cloud and SaaS apps – places where traditional approaches to security simply cannot provide adequate protection.  This security shortfall leads to compromised customer records, stolen data, and millions lost in breaches – just to name a few. 


Holistic Security Centered on Identity

Deep Learning Summer School, Montreal 2016

  • Learning to See Learning to See
  • Learning to Communicate with Deep Multi–Agent Reinforcement Learning Learning to Communicate with Deep Multi–Agent Reinforcement Learning
  • Deep Reinforcement Learning Deep Reinforcement Learning
  • The Deep Learning Summer School 2016 is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.
  • Learning Deep Generative Models Learning Deep Generative Models

Read the full article, click here.


@karpathy: “Videos from 2016 Deep Learning Summer School in Montreal are up and slides”


Deep neural networks that learn to represent data in multiple layers of increasing abstraction have dramatically improved the state-of-the-art for speech recognition, object recognition, object detection, predicting the activity of drug molecules, and many other tasks. Deep learning discovers intricate structure in large datasets by building distributed representations, either via supervised, unsupervised or reinforcement learning. The Deep Learning Summer School 2016 is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research. Note: Slide synchronization will soon be added.


Deep Learning Summer School, Montreal 2016

Design Patterns for Deep Learning Architectures

Design Patterns for #DeepLearning #Architectures. #BigData #MachineLearning #DataScience #AI

  • We purposely use “pattern language” to reflect that the field of Deep Learning is a nascent, but rapidly evolving, field that is not as mature as other topics in computer science.
  • Each pattern describes a problem and offers alternative solutions.
  • You can find more details on this book at: A Pattern Language for Deep Learning
  • Pattern Languages are languages derived from entities called patterns that when combined form solutions to complex problems.
  • There are patterns that we describe that are not actually patterns, but rather may be fundamental concepts.

Read the full article, click here.


@gp_pulipaka: “Design Patterns for #DeepLearning #Architectures. #BigData #MachineLearning #DataScience #AI”


Deep Learning can be described as a new machine learning toolkit that has a high likelihood to lead to more advanced forms of artificial intelligence. The evidence for this is in the sheer number of breakthroughs that had occurred since the beginning of this decade. There is a new found optimism in the air and we are now again in a new AI spring. Unfortunately, the current state of deep learning appears to many ways to be akin to alchemy. Everybody seems to have their own black-magic methods of designing architectures. The field thus needs to move forward and strive towards chemistry, or perhaps even a periodic table for deep learning. Although deep learning is still in its early infancy of development, this book strives towards some kind of unification of the ideas in deep learning. It leverages a method of description called pattern languages.


Design Patterns for Deep Learning Architectures