Artificial intelligence and Machine Learning has its deep roots in Computer Science. Before starting with course for Artificial Intelligence one should know more about Machine Learning Vs Artificial Intelligence. In this article, we are discussing about the basic points through which we can differentiate between these two terms. The deep reinforcement learning comprises of the deep artificial neural networks guided by the codes. It requires a deep analogical reasoning to understand these codes and guide them according to the command. In future, the Artificial intelligence market will grow to $5.05 billion by 2020. Such stats has reassured our faith in the accelerating power of the human governed technologies.

Witnessing the staggering stats, we should imagine the scenario with the machine learning developer’s point of view. But some people misunderstand that AI and ML are the same things but in different manners. This perception is completely wrong. AI and ML are the two branches of computer science. Their working and perspective is entirely different.

AI Deep Learning

The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial means something which is develop in laboratory by the human or intelligence means ability to understand things. Artificial intelligence in a whole is not a system. AI implements in the system. To make things clear to the layman, AI is call so that everyone can understand the basic idea. In one definition, AI means.

“The study to train the computers so that computers can perform the task better than the human beings”

Hence, it is an intelligence to add the functionalities and capabilities to machine that human has.

Machine Learning

Machine learning is the learning that machine can learn by itself without any external interference. It implements through application and it provides the ability to learn and improve from its surroundings. ML scientists generate a program by integrating the input and output variables of the program. Rules engines are used in the machine learning. Expert system knows to perform better in the extreme circumstances.

The simple definition of machine learning is:

“Machine learning is to learn from experience W w.r.t some class of task T and performance measure of P. It improves with the experience day by day”

Hence, Machine Learning is all about machines learning from its own surroundings.

Whereas, Artificial Intelligence is the software that is installed in the system to perform the task.

To make things clear. let’s draw a line and explain the definitions in tabular manner. This further differentiate  between Machine Learning Vs Artificial Intelligence.

Why do people related machine learning with Artificial intelligence?

There is a fine line between AI and ML. It is all about the neuron network of the machine. Image recognition is the example of difference between AI and Machine Learning. The AI camera is designed to capture the face in low light. But it should not capture the face on the billboard. The camera should know that it has to click the living picture not the captured already drawn. AI is clicking human face and machine learning is development of camera not to click the human like face. Natural language processing is the process of development of neuron network to be capable enough to develop the language by its own. People relate machine learning with AI, However they has a fine line between. This fine line that we have discussed above in the table can cause confusion among the people who are ‘laymen’.

What to choose between AI and ML?

In a simple way, you do not have any option. Yes it’s true. These both terms are the children of the same parent and with parent who is known as computer science, children are complementary. If you want specific answer, then Machine Learning is the answer as it will automatically cover your AI. It is like buying an apartment and getting windows free of cost. Which is obvious.

Conclusion

The advances made by the expert systems creates a knowledge graph or symbolic AI. Through the deep reinforcement learning AI creates a deep artificial neural networks. Through the years of research, the scientists has concluded that Machine Learning can create natural language processing. It means, AI and ML can create faster than our expectations. Now, only the prediction of future is left and we are chasing the benchmarks of artificial intelligence like nuclear fission. By combining the Artificial intelligence and Machine Learning, we can combine Bayesian and evolutionary methods to show the correct path of the analogical reasoning. Symbolic reasoning is directly proportional to the AI methods and Machine Learning.

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