Solved – the difference between Machine Learning and Deep Learning

Question

OK, I know there is a lot of topic regarding this in the internet, and trust me, I've googled it. But things are getting more and more confused for me.

From my understanding, Deep Learning (DL) is kind of a subset of Machine Learning (ML) where ML can consist of something like Support Vector Machines and DL can be consists of something like Convolutional Neural Network.
Is this correct?

If I want to getting start at this, what should I read first? What kind of research paper that can I read?

Answer 1

Starting with the first page of Goolge Scholar, one finds some promising abstracts.

I. Arel,D. C. Rose, T. P. Karnowski Deep Machine Learning - A New Frontier in Artificial Intelligence Research

This article provides an overview of the mainstream deep learning approaches and research directions proposed over the past decade. It is important to emphasize that each approach has strengths and "weaknesses, depending on the application and context in "which it is being used. Thus, this article presents a summary on the current state of the deep machine learning field and some perspective into how it may evolve. Convolutional Neural Networks (CNNs) and Deep Belief Networks (DBNs) (and their respective variations) are focused on primarily because they are well established in the deep learning field and show great promise for future work.

Yann LeCun, Yoshua Bengio & Geoffrey Hinton, Deep Learning, Nature

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

@frankov suggested adding this diagram which summarizes one interpretation of the different flavors of machine-learning.