Machine Learning

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MACHINE LEARNING
UNREVIEWED SUMMARY:

Machine Learning Definition :
Machine learning is a field of computer science. It is also a type of Artificial Intelligence that enables the programmers to write programs in a more simple way. It focuses more on developing programs that teach computers to change when exposed to new data and to grow. Its goal is to understand and follow the methods by using algorithms to do that task automatically without any human assistance.
In 1959, Arthur Samuel defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed".

What is the history of Machine Learning?
You can view ML's history by clicking on this link:
http://sge.wonderville.ca/machinelearning/history/history.html

What are the advantages of Machine Learning?
ML is being used increasingly, and there are many reasons for this.
1- The machine will eventually improve itslef from its own mistakes.
2-Faster than people, so it saves time. 3-This took several years by working on it antil it gets it right by many parameters.
4- It is widely used in face recognition and also captioning photos. It is used to capture thieves, or anyone involved in a crime scene from the camera.

What are the disatvantages of Machine Learning?
It is not guaranteed that ML algorithms will always work for every case. Sometimes ML will fail, so it needs to understand the problem at hand to apply ML algorithm in the right way. Some ML algorithms require alot of data such as deep learning algorithms. It might be exhausting to gain this large amount of data. Fortunately, there is alot of data for training purposes and image recognition.


Knowing when and how to use a specific machine learning algorithm is important. There are simple and complex machine learning algorithms, so it's important to choose wisely between them.

Some applications of Machine Learning:
1-ML is used for recognizing photos, video, and texts. 2-It has been used in google translate, the new feature is to take a photo of any text or paragraph you want to translate, it recognizes the text, and highlights it, afterthat the person chooses the words or the text that is needed to ba translated. 3-ML recognizes speech. It has been used in many applications, such as google, skype, and siri. 4-Speech recognition can be used to translate to different language, or writing subtitles, or even in reacting with your smart phone! It has been widely used in many applications. Such as google, skype, and Siri.
5-Identufying people by face recognition algorithms, it is where the computer identifies an individual from a photo, this feature can be found on facebook for automatically tagging people 6-ML solves issues after many trials and after giving the algorithm many datasets so that it can predict what other datasets are, we keep on giving it examples till the computer gets it right. 7-ML can diagnose a patient whether sufferring or not of some disease, it hepls the nurses and doctors in the hospitals in diagnosing the patients,it is not that accurate in diagnosing, but experts are trying to improve ML in medicine. 8-ML is used in weather prediction. ML is applied to forecast weather.

REVIEWED SUMMARY:

Machine Learning Definition :
Machine learning is a field of computer science. It is also a type of Artificial Intelligence that enables the programmers to write programs in a more simple way. It focuses more on developing programs that teach computers to change when exposed to new data and to grow. Its goal is to understand and follow the methods by using algorithms to do that task automatically without any human assistance.
In 1959, Arthur Samuel defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed".

What is the history of Machine Learning?
You can view ML's history by clicking on this link:
http://sge.wonderville.ca/machinelearning/history/history.html

What are the advantages of Machine Learning?
ML algorithms are increasingly being used, and there are many reasons for this. The main reason is because ML has a system that is trained on some datasets that will eventually learn and improve if given a certain task. ML is so faster than humanbeings, it invests time and teaches itself from the data that is given to the machine, or from the mistakes it does. This took several years of working on it until it gets it right by many parameters. In present, ML is used to discover the features of relevant data in disordered datasets. Those features are useful for some applications of ML , as face recognition.

What are the disatvantages of Machine Learning?
It is not sure that ML algorithms will always work for every case. Sometimes ML will fail, so it needs to understand the problem at hand to apply ML algorithm im the right way. Some ML algorithms require alot of data such as deep learning algorithms. It may be exhausting to gain this large amount of data. Fortunately, there is alot of data for training purposes and image recognition.


Knowing when and how to use a specific machine learning algorithm is important. There are simple and complex machine learning algorithms, so it's important to choose wisely between them.

Some applications of Machine Learning:
ML is used for recognizing photos, video, and texts. As it has been used in google translate, the new feature is to take a photo of any text or paragraph you want to translate, it recognizes the text, and highlights it, afterthat the person chooses the words or the text that is needed to ba translated. ML recognizes speech as well.has been used in many applications, such as google, skype, and siri. Speech recognition can be used to translate to different language, or writing subtitles, or even in reacting with your smart phone! It has been widely used in many applications. Such as google, skype, and Siri.
It is also used in identifying people by face recognition algorithms, it is where the computer identifies an individual from a photo, this feature can be found on facebook for automatically tagging people, it is also used to arrest thieves or criminals. ML solves issues after many trials and after giving the algorithm many parameters or datasets so that it can predict what other datasets are, we keep on giving it examples, till the computer gets it right by itself, it also learns from its mistakes and does not repeat them again. ML can diagnose a patient whether sufferring or not of some disease, it hepled the nurses and doctors in the hospitals in diagnosing the patients,it is not that accurate in diagnosing, but experts are trying to improve ML in medicine. ML is used in weather prediction. ML is applied to forecast weather, and experts are also trying to improve the quality of prediction.

Here are some links if you want to know more about ML:
1-Click here to watch the video
2-Machine Learning pdf
3-wikipedia
4-Artificial Intelligence: Machine Learning
5-Theoritical Machine Learning pdf

Questions about Machine Learning:
1-From where did the idea of ML come ?
2-What was the first reason for Machine Learning?
3-Can we substitute people with Machine Learning in the upcoming years?

Resources:
-Arthur Samuel's Definition from:
https://en.wikipedia.org/wiki/Machine_learning
-https://www.quora.com/What-are-the-advantages-and-disadvantages-of-machine-learning -https://www.quora.com/What-are-some-interesting-possible-applications-of-machine-learning