Differentiate between machine learning and deep learning :-
Machine learning :-
1. Works on a small amount of datasets for accuracy.
2. Dependent on low and machine.
3. Divides the task into sub- tasks, solves them individually and finally combine the result.
4. Takes less time to train.
5. More than to test the data.
Deep learning :-
1. Works on large amount of datasets.
2. Heavily dependent on high end machine.
3. Solve problem end to end.
4. Takes more time to train.
5. Less time to test the data.
Applications of deep learning :-
1. Automatic text generation :
a. Corpus of text is learned from this model new text is generated, word - by - word, character - by - character.
b. When the model is capable of learning how to spell, punctuate, from sentences, or it may even capture the style.
2. Healthcare :- Helps in diagnosing various disease and treating it.
3. Automatic machine translation :- Certain words, sentences or phrases in one language is transformed into another language.
4. Image recognition :- Recognizes and identifies peoples and objects in images as well as to understand content and context. This area is already being used in gaming, retail, tourism, etc.
5. Predicting earthquakes :- Teachers a computer to perform viscoelastic computations which are used in predicting earthquakes.
Applications of artificial intelligence :-
1. Gaming :- AI plays crucial role in strategic games such as chess, poker, tic - tac - toy, etc., where machine can think a large number of possible positions based on heuristic knowledge.
2. Natural Language Processing :- It is possible to interact with the computer that understands natural language spoken by humans.
3. Expert systems :- There are some applications which integrate machine software, and special information to impart reasoning and advising. They provide explanation and advice to the users.
4. Vision systems :- The systems understand, interpret, and comprehend visual input on the computer.
5. Speech recognition :- Some intelligent system are capable of hearing and comprehending the language in term of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human's noise due to cold, etc.
6. Handwriting recognition :- The handwriting recognition software read the text written on paper by a pen or on screen by stylus. It can recognize the shapes of the letters and convert it into editable text.
7. Intelligent robots :- Robots are able to perform the task given by human. They have sensors to detect physical data from the real world. They have efficient processors, multiple sensor and huge memory, to exhibit intelligence.
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