Deep Learning is the application of unsupervised learning paradigms to machine learning capabilities in order to identify, extract, and leverage features leading to insights that enable actionable outcomes. While computer science is a relatively young discipline, Deep Learning is even a young discipline within this field.

Deep Learning is one of the more remarkable resources available to research and practitioners in this emergent field. The goal of the website is to host a variety of resources and pointers to information about Deep Learning. In these pages you will find:

  • reading lists of relevant article and books,
  • links to software and tools,
  • datasets and databases,
  • a list of deep learning research groups and labs,
  • a list of announcements for deep learning related jobs (job listings),
  • as well as tutorials and cool demos.


For example, under the “Recent Post” section, there is an interesting article “An Article about History of Deep Learning.” The author, Daniela Hernandez, describes how deep learning has been an disciplinary outlier in the academic field for the last 3 decades. Emerging from this intelligence slumber, most practitioner are merely “fashioning artificial neural networks that mimic at least certain aspects of the brain.” While not much of an advancement in unsupervised learning, it nevertheless has extended our ability to creates intelligence systems that scale with minimal human interaction.

Like deep learning itself, this is a relatively young site that should mature over time, becoming a key resource in the data science field.


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