Deep learning is a learning scheme that approaches the learning problem by learning the underlying representations; too much of learning. I thats why its also called as representation learning.
A technique for implementing machine learning. At the same time I also claim It is absolutely wrong to call Deep Learning as Machine Learning (in my personal opinion). The techniques is to achieve a goal not necessarily come out of same goal. #AILabPage
Does GDPR require Machine Learning algorithms to explain their output? may be yes may be no or in short Probably not, but there is enough ambiguity to be clarified and keep DataScientists, Lawyers, industry influencers busy.
Astonishing Hierarchy of Machine Learning Needs – Artificial intelligence and machine learning are used interchangeably often but for they are not the same. Machine learning is one of the most active areas and a way to achieve AI. Why ML is so good today; for this, there are a couple of […]
Reinforcement learning can be understood by using the concepts of agents, environments, states, actions and rewards. This is an area of machine learning; where there’s no answer key, but RL agent still has to decide how to act to perform its task. The agent is inspired by behaviourist psychology who decide how and what actions will taken in an environment to maximize some notion of cumulative reward.