What is the difference between AI(Artificial Intelligence) and ML(Machine Learning)?
Most of the times Artificial Intelligence(AI) and Machine Learning(ML) are used interchangeably but they are two distinct terminologies.
AI is an umbrella term under which ML lies. AI is a broad concept which focuses on building smart/intelligent machines/robots/software systems.
ML is a process by which a machine auto trains itself for achieving a certain objective over datasets. While going through multiple iterations, machines get more and more refined intelligence, in an autonomous fashion. Machines learn and improve its accuracies eventually. ML allows machine to recognize patterns and make predictions.Some real world examples of ML are speech recognition/conversational technologies, language translations, object recognition and other tasks.
There are underlying concepts like Automated Speech Recognition(ASR) and Natural Language Processing(NLP) in AI which overlap with ML.
Deep Learning(DL) is a subset/class of ML algorithms which involves ANN(Artificial Neural Networks). Learning can be supervised, semi-supervised or unsupervised. DL concepts can be applied in image processing, speech recognition, designing drugs, board games, machine translations etc.
The intent of this post is to pick these really complex topics at a very high level rather deep diving each one of them.
AI is an umbrella term under which ML lies. AI is a broad concept which focuses on building smart/intelligent machines/robots/software systems.
ML is a process by which a machine auto trains itself for achieving a certain objective over datasets. While going through multiple iterations, machines get more and more refined intelligence, in an autonomous fashion. Machines learn and improve its accuracies eventually. ML allows machine to recognize patterns and make predictions.Some real world examples of ML are speech recognition/conversational technologies, language translations, object recognition and other tasks.
There are underlying concepts like Automated Speech Recognition(ASR) and Natural Language Processing(NLP) in AI which overlap with ML.
Deep Learning(DL) is a subset/class of ML algorithms which involves ANN(Artificial Neural Networks). Learning can be supervised, semi-supervised or unsupervised. DL concepts can be applied in image processing, speech recognition, designing drugs, board games, machine translations etc.
The intent of this post is to pick these really complex topics at a very high level rather deep diving each one of them.
