Machine Learning In Artificial Intelligence through Software Developers Perspective
Now a days Artificial Intelligence is really hype in the market . Every one is talking about it and its future usage in human life .As we have seen software has absorb our life in it . we are surrounded by software's from our watches to mobile , Television , Cars everywhere . Machine learning has potential to absorb all software . Means every software can use benefits of machine learning in it. Use of machine in software's is increasing day by day in exponential manner. So to me as a software engineer people generally ask me following questions about machine learning.
- What is Machine learning ?
- Where it came From ?
- How does it work ?
- Where it is used in our daily life ?
- How many types of machine learning are there ?
What is Machine Learning (Artificial Intelligence) ?
Machine Learning as the name suggest you can make machine learning things by itself . It is techniques through which you make your computer or machine to learn from its data or its mistake as we human do . It make machine as human in learning process so that all those task where human are needed that can be replaced by machines. Through machine learning you can make all those task possible which was previously not possible or very difficult to achieve through software . As as example to make machine to judge persons emotion through its comment on imbd or facebook or to make machine to recognize image and predict objects present in the image .
Where Machine Learning Came from ?
Machine learning is not new field . It is one the of the oldest fields.Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term "Machine Learning" in 1959 while at IBM. As a scientific endeavour, machine learning grew out of the quest for artificial intelligence. Already in the early days of AI as an academic discipline, some researchers were interested in having machines learn from data. They attempted to approach the problem with various symbolic methods, as well as what were then termed "neural networks"; these were mostly perceptrons and other models that were later found to be reinventions of the generalized linear models of statistics.Probabilistic reasoning was also employed, especially in automated medical diagnosis
Machine learning, reorganized as a separate field, started to flourish in the 1990s. The field changed its goal from achieving artificial intelligence to tackling solvable problems of a practical nature. It shifted focus away from the symbolic approaches it had inherited from AI, and toward methods and models borrowed from statistics and probability theory. It also benefited from the increasing availability of digitized information, and the ability to distribute it via the Internet.
How Machine Learning works ?
Machine Learning is a technique through which you make software's through data . If you have less or no data then you cannot implement make software using it . It works as a human child . As you have to make something learn by child you have to show that thing to him 100 times and says name of it then child mind will associate that picture with that name in there mind . And after that when ever child see that things in future he will associate that picture with the name which is there in his mind . As s Example let say you want to make your child learn that this product is an apple.
you have to show him hundred times and tell him that this is an apple. Likewise to make machine learning to learn that this product is an apple . you have to train machine with 100 different images of apple to make it learn that this product is an apple . After seeing it 100 times let say it will learn that this product is an apple . Next time when ever machine see it will recognize it that this is apple .
Where it is used in daily life ?
As software is used every corner of our life . machine learning will be used in every software in future . Right now many software has adopted it from search engines to our personal assistance in our mobile like siri , Alexa . All uses machine learning (Deep learning) in it. It is used in all major companies product and each has launched its own designed open source machine learning frameworks some of the popular available in the market are Tensorflow , CNTK , PYTORCH , ALEXA . All have contributed to machine learning community.
Google , Microsoft , Apple use machine learning in their personal assistance as Google assistance , Cortana , SIRI to interact with the human . Machine learning gives this assistance power to recognize your words which you tell to them and respond to it effectively . Google uses machine learning in its search engine to provide you results effectively. it also use machine learning in language translation from one language to other languages . Facebook uses machine learning to recognize you and tagging you in all photos where you are present on facebook. It also provides you post which relevant to your choices .Most Importantly google, facebook , microsoft uses Machine Learning to shows you advertisement based on your choices which gives company a big profit . E-commerce sites such as amazon and others uses Machine learning (ML) to show you best products with best price of your choices to you . Youtube uses ML to provide you best videos of your choice . List is increasing day by day as new algorithms are implemented . You Activites on internet is monitored to take more advantages out of it by the companies . Each day many software developer are switching to machine learning .
How many types of machine learning are there ?
There Are Mainly three type of machine learning types are there :
- Regression Learning
- Supervised Learning
- Unsupervised Learning
In the upcoming posts i will be sharing with techniques and methods to learn machine learning as an software engineer. how not to go in full details and just to learn methods which is useful to use machine learning in your existing softwares or create full new software based on machine learning .
Deep learning Engineer