It is a class of machine learning where theories of the subject aren't strongly established and views quickly change almost on daily basis. "I think people need to understand that deep learning is making a lot of things, behind the scenes, much better" – Sir Geoffrey Hinton Deep Learning can be termed as the best confluence of big data, big models, big compute and big dreams. Deep Learning is an algorithm that has no theoretical limitations of what it can learn; the more data and the more computational (CPU power) time you give, the better it is – Sir Geoffrey Hinton. AILabPage defines Deep learning is "Undeniably a mind-blowing synchronisation technique applied on the bases of 3 foundation pillars large data, computing power, skills (enriched algorithms) and experience which practically has no limits". Deep Learning is a subfield of machine learning domain.
Machine Learning Algorithms – DataScientist may be the sexiest job of today but the understanding, implementation, applied ML experience is missing. Having the top algorithms on your fingertips in real business is missing big time. The real job for any data scientist is the ability to clarify, demonstrate, extract real values out of data and reap rewards. "Machine Learning" as a basic skill sounds like teleportation tool to many businesses especially for the companies which are actually data factories i.e social media platforms. Describing and picturising the top few machine learning algorithms is the main idea of this post.
Artificial Neural Networks – As the name suggest "Neural Network", they are inspired by the human brain system. ANNs were originally designed with biological neurons as a reference point thus sometimes they are called a brain model for computers. ANNs can process information in form audio, video, images, texts, numbers or in any form of data. Neurons i.e. perceptrons (as known in early days) were staged as a decision function in those times. Artificial Neural networks are designed to take several binary inputs to give a binary output.
Recurrent Neural Networks – Main use of RNNs are when using google or facebook these interfaces are able to predict next word what you are about to type. RNNs have loops to allow information to persist. RNN's are considered to be fairly good for modeling sequence data. Recurrent neural networks are linear architectural variant of recursive networks. This post is a high level over view for creating basic understanding.