So basically on the first look, everyone thinks the same, but as you dig "deep", you will know that AI(artificial intelligence) is the superset of them all. ML is the subset of AI and deep learning is the subset of ML.
In AI, your aim is to design agent which can learn from the surrounding environment to improve itself. In ML, as you give more data to the program, it learns from data, tries to find co-relations between variables and then try to predict answers for unseen examples. In deep learning, you try to solve the above problems using multi-layer neural networks.
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So basically on the first look, everyone thinks the same, but as you dig "deep", you will know that AI(artificial intelligence) is the superset of them all. ML is the subset of AI and deep learning is the subset of ML.
In AI, your aim is to design agent which can learn from the surrounding environment to improve itself. In ML, as you give more data to the program, it learns from data, tries to find co-relations between variables and then try to predict answers for unseen examples. In deep learning, you try to solve the above problems using multi-layer neural networks.
Here is nice article to get you started:
The Difference Between Artificial Intelligence, Machine Learning, and Deep Learning
Thanks blackbird. I will try to make most of it.
AI - Non-biological way of solving complex problems.
ML - The way of solving more complex problems today than yesterday through yesterday' learnings.
DL - The subset of ML that is inspired by human brains.
For me all the above words look same and confusing.