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What is Supervised Machine Learning? In Supervised Machine learning, the Machine is given a set of data which already knows how the output should look and have an idea about the relation between the input and out. Supervised learning problems are also categorized as “regression” and “classification” problems. In regression problems machine predict a numeric or continuous variable output where as in classification problems the predicted output is discrete.  For example, if the...

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What is machine learning?   Here’s a basic definition of machine learning: “Algorithms that parse data, learn from that data, and then apply what they’ve learned to make informed decisions” An easy example of a machine learning algorithm is an on-demand music streaming service. For the service to make a decision about which new songs or artists to recommend to a listener, machine learning algorithms associate the listener’s preferences...

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Do we need to study traditional computer vision since deep learning can handle anything more efficiently?   These are good questions. Deep learning (DL) has certainly revolutionized computer vision (CV) and artificial intelligence in general. So many problems that once seemed improbable to be solved are solved to a point where machines are obtaining better results than humans. Image classification is probably the prime example of this....

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Data mining is a big business. These times everything is analysed. Everyone is analysing mouse clicks, mouse movements, customer purchase patterns. Such analysis has proven to give profitable insights that are driving businesses further than ever before. Big companies such as google, amazon and Facebook are in heavy use of it. It is used to keep track of customers and feed the   Data can be mined...

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In these times, computer vision is growing as never before. Many things can be mentioned as a reason, but in my view the main reasons are the following: Advancements in hardware The emergence of deep learning The advent of large datasets The increase in computer vision applications   Better and More Dedicated Hardware One of the main reasons why image processing is such a difficult problem is that...

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There are many many deep learning models out there doing various things. Depending on the exact task they are solving, they may be made differently. Some uses convolution followed by pooling. Some uses several convolutional layers before there is any pooling layer. Some uses max-pooling. Some uses mean-pooling. Some have a dropout added. Some have a batch-norm layer here and there. Some uses sigmoid neurons,...

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