Artificial Intelligence Machine learning and Deep learning are three different terms. and I am sure that you should be confused in your mind between them. So today I am going to explain to you what are these three terms. First of all guys please read this post at the end of the word because without reading totally post you wouldn’t understand what I am saying.
Artificial Intelligence is a big term under which Machine learning and Deep learning come. Machine learning is a subset of Artificial intelligence. and Deep learning is a subset of Machine learning. So we can say that all three parts are a subset of each other.
So take a deep look to understand these three terms…
What is Artificial Intelligence?
The term AI(artificial intelligence) was first existence in 1956. and within days it’s become a popular subject in research.
Artificial Intelligence is a technique in which machines act like a human. and the machines have their own brain and can take decisions by themself.
Artificial Intelligence is used to perform human tasks by a machine and AI can be made by processing a large amount of data with patterns.
but at the beginning of time, this idea totally failed. because human doesn’t know how to prepare a machine code for an AI machine so because of this reason machine learning comes into existence.
What is Machine Learning?
Machine learning comes into existence in the early nineties. and the main aim of Machine learning is how to train a robust version of the Artificial Intelligence system which is able to perform tasks like a human. and in machine learning, the problem is that we need to collect a big amount of data for a machine.
because the machine only performs with codes and with the term of a large amount of data Statistics and Neuroscience come into existence and the statistics are used for making complex models with a huge amount of data and the Neuroscience is used to design models of the brain for machines using neurons just like our brain.
So machine learning is a subset of Artificial Intelligence in which machines used the statical method and probability methods to adjust which task a machine will be performed after a sudden task and this term enables the machine to improve the machine code with experience.
Example: A car that is automatically derived is running on the road. so when the road turns the car also turns automatically. this is possible because of Machine learning. but the fact is that machine learning only works on conditions. it has not the ability to think on its own.
But there is a fault that is machine consumes a large amount of time to complete a task. So, because of this, Deep learning comes into existence.
What is Deep Learning?
Deep learning is also a kind of Machine learning and it’s a part of Machine learning. in Deep learning, we only focus on the concept of Artificial Neural Networks. we perform the functionality of Neurons to make the brain of a Machine.
We can simply connect all the neurons in a systematic form and connect each other according to data patterns. and the fact of Deep learning is that the working of Neurons is not depending on a specified algorithm.
Another thing is that Neurons are just like a black boxes because no one knows what is going on Neurons. Deep learning is a way to think about a big part of a particular object because Machine learning only works under certain conditions.
For an example of how a machine should know wheater, an object is a dog or cat. here Machine learning fails. because Machine learning is only checked certain conditions if an object is small and has four legs and a tail. so that object is a dog but these conditions also work on a cat. so Machine is going to confuse. so here Deep learning is work. because Deep learning is used more valuable data.
Deep learning is used a large amount of data to make sure about an object. whereas Machine learning can easily work with small data.
Deep Learning Vs Machine Learning.
The execution time of a task in Deep learning is much less than in Machine learning. Deep learning depends on and only works with higher-perfection machines where Machine learning also works with lower-perfection machines.
Machine learning breaks down a problem and solves the part of the problem and combined them together to produce the output. but Deep learning is used end-to-end methods to solve a problem.
So the main theme is that Machine Learning is used algorithms to collect data and learn from data, and makes the decision based on his learning.