There are up to ten different imaging operations (auto focus, lighting corrections, color filter array interpolation etc.) Automatic image captioning is the task where given an image the system must generate a caption that describes the contents of the image. Since it is a classification based algorithm, it is used in many places. For Example, Image and Speech Recognition, Medical Diagnosis, Prediction, Classification, Learning Associations, Statistical Arbitrage, Extraction, Regression. The raw data can come in all sizes, shapes, and varieties. It is also one of the most efficient algorithms used for smaller datasets. Simple applications of CNNs which we can see in everyday life are obvious choices, like facial recognition software, image classification, speech recognition programs, etc. One of the most common uses of machine learning is image recognition. It’s a process of determining the attitude or opinion of the speaker or the writer. Sentiment analysis is another real-time machine learning application. There are many situations where you can classify the object as a digital image. The Large Scale Visual Recognition Challenge (ILSVRC) is an annual competition in which teams compete for the best performance on a range of computer vision tasks on data drawn from the ImageNet database.Many important advancements in image classification have come from papers published on or about tasks from this challenge, most notably early papers on the image classification … Modern Computer Vision technology, based on AI and deep learning methods, has evolved dramatically in the past decade. These are the real world Machine Learning Applications, let’s see them one by one-2.1. There are lots of examples out there where the techniques of classification and clustering are being applied, in fact in plain sight. In the above examples on classification, several simple and complex real-life problems are considered. Text analysis, as a whole, is an emerging field of study.Fields such as Marketing, Product Manageme n t, Academia, and Governance are already leveraging the process of analyzing and extracting information from textual data. Today it is used for In other words, it’s the process of finding out the emotion from the text. There are many applications of SVM. Some of the machine learning applications are: 1. I will just mention a few. How Adversarial Example Attack Real World Image Classification In this article, we will be discussing about various SVM applications in real life. Classification problems are faced in a wide range of research areas. Hence, now we have a clear understanding on how to work with SVM. In 2014, there were an explosion of deep learning algorithms achieving very impressive results on this problem, leveraging the work from top models for object classification and object detection in photographs. 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