In one of my recent e-commerce project, our customer has asked to implement some AI techniques to suggest best mobile phones from catalog database by writing Machine learning algorithm based upon the search inputs e.g. phone picture, camera, music, price, size and battery power etc. The result must bring output to suggest users with the brand name and ratings and also allow users to compare features of all models available in the same price and configuration range. To develop this AI based solution it was not clear whether to use Machine Learning or Deep learning algorithm or both. The task for extracting text using data mining technique and process them to compare with other models was understood using NLP techniques but identifying the phone object to get the details of phone was quiet a lot challenging. In AI world, to detect an object whether car, signal, pedestrian, phone, laptop etc. we need to go an extra mile by extending our algorithm design from Machine learning to Deep learning approach such as python based R-CNN Algorithms for Object detection. To understand the difference between AI, ML and DL in my e-commerce project I have tried to extract the correct definition of each from the web which has made my job easier to finish the project with accurate output and customer expectation. AI is a ability of computer program to function like a human brain means AI can be loosely interpreted to mean incorporating human intelligence to machines. AI based machine can sometimes think and behave like human brain right from recognizing an object and decide about the next step to solve the problem associated with that. For e.g. if user shows an object like car, AI will detect the object and suggest various options from buying, selling or renting a car from the listed authorized dealers. Another AI based example is Speech recognition software used by Amazon, Google and Microsoft to develop chat bot applications to provide help-desk and customer care support to it's various clients. People always relate AI with Machine learning and Deep Learning to develop AI based application in their organization. Machine learning and Deep learning allows programmer to write algorithms and create trained models to create AI based solution. So it would be wise to say ML is a subset of AI and DL is a subset of ML. All AI powered machines are usually classified into two groups general and narrow. The general artificial intelligence AI machines can intelligently solve problems, like the ones mentioned in my e-commerce project using NLP technique. The narrow intelligence AI machines can perform specific tasks very well, sometimes better than humans though they are limited in scope. The technology used for classifying images is an example of narrow AI. Now let us discuss more about Machine learning and Deep learning concepts which acts as a subset to AI. Machine learning is the ability to enable a machine to learn by itself. For e.g. if you want to train a machine to identify OCR digit between 0-9 you need to train model with all combinations of OCR images and pixels of each digit with respect to font, size, color and pattern. Once the model is trained based upon data source, AI will be able to detect the correct digit from the OCR image. Such kind of trained model in ML can be used to read vehicle number from the number plate at various toll plaza and mall for collecting parking fees. The same trained model can be also used to send penalty message to the offender who has jumped the traffic signal by violating the traffic rules. Deep learning or DL is advanced version and subset of ML. It extends ML to enable auto learning features e.g. Automatic car driving uses Deep learning algorithm which cannot be done simply by using Machine learning algorithm. There are many examples which can be discussed further to explain the difference between AI, ML and DL in current perspective and it is left to us to pick up the best algorithm to come out with a robust and advanced AI based solution which a customer can use to improve his business in an efficient manner.
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