Deep learning – Artificial Intelligence And Machine Learning

Artificial intelligence is the simulation of human intelligence in machines. The machines are customized and designed to think like human beings. It is a term applied to any machine exhibiting characteristics associated with the human mind, such as learning and problem-solving. These systems are characterized by its ability to rationalize and take actions having a good chance of achieving a specific goal. The applications are endless. The technology can be applied to an ocean of different sectors and industries. It is a boon in the Healthcare industry as it is affecting and creating new systems of treatment and surgical procedures (Frankenfield, 2019).

Let us take the example of playing chess or self-driving. In both of these cases the consequence of any action impacts the end result. In chess the result is winning the game but for self-driving, the technology needs to account for the external data and compute it in a way preventing collision and reaching the destination securely. Machine learning adds value to the artificial intelligence systems enhancing their performance by the incorporation of automated learning and improvising decision making.The biggest advantage of machine learning is that it doesn’t require to be explicitly programmed. It composes of certain algorithms carrying out the work of automated learning effectively (Gupta, 2019). The process of learning starts with the observation of data. Machine learning methods use algorithms to learn effectively.

The algorithms content in machine learning covers all the aspects of automated learning each algorithm is a complex set of programs automated is a function. The algorithms are generated in a way to cover all the probabilities associated with proper and good decision making. All in all these algorithms prevent the usage of AI systems from being explicitly programmed. Machine learning algorithms are composed of supervised learning, unsupervised learning and reinforcement learning (Dasgupta & Nath, 2016).

These three branches are learning mechanisms promoting automated learning and improvising with prior experiences. Empowered with these set of algorithms machine learning is a technology to be reckoned with. It can be said that artificial intelligent (AI) systems are evolving due to machine learning.Deep learning is an artificial intelligence function replicating the workings of a human brain in the aspect of creation and processing of data and patterns. The use of decision making is inherent in deep learning.It is identified as a subset of machine learning known as deep neural learning for a deep neural network.

Deep learning, machine learning and artificial intelligence can be imagined as a set of Russian Dolls nested within each other (Hargrave, 2019). In the end, we come to the conclusion that all machine learning is AI, but all artificial intelligence is not machine Intelligence and so forth. To put it in realistic terms machine learning and deep learning are invented to improve the learning mechanism of artificial intelligence systems. Deep learning is a more advanced subset of machine learning where the algorithms are richer and complex affecting the computer decision making and the result.

Deep learning is all about neural networks and concern more with neuron layers and interconnectivity (Ganguly, 2019). There is still a long way for machines to mimic the human brain and all its complexity, but we are in the direction. To put it in plain simple terms deep learning is a technique for the implementation of AI, machine learning is also an art and science by itself, but it does not have the power, and the complex deep learning brings to the system. Deep learning is more specific for example speech recognition is possible only by a complex neural network.

Machine learning mostly concerns itself with static vehicles where deep learning goes a step beyond and includes autonomous vehicles (Garbade, 2018). For instance, before vehicles can determine or compute their next action it needs to recognize all the vehicles and the road signs that are around it in order to do so the standard machine learning techniques are not enough.

DL is a technique for realizing machine learning. In other words it can be put as the evolution of machine learning. DL algorithms are inspired by the information processing patterns found in the human brain. On receiving new information, the human brain tries to compare it to past item before making sense of it (Jeffcock, 2018). This same concept is applied by deep learning algorithms. Complex neural networks are the backbone of deep learning process. These Technology systems should never be manipulated or used against human resources as depicted. They should always go in line with the human endeavour and be a support system for us to reach far where the human mind cannot reach