Machine Learning And Artificial Intelligence: Essential Guide To Understanding How ML And AI Can Be Applied In Practice And Be Compatible With Human Behaviour In Modern Times by Chris Neil
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Overview: Machine learning is a data-driven approach. Hence it implies the availability of large datasets in order to make accurate decisions. In case only a limited dataset is available to solve a particular problem, it is best to use a deterministic approach. When a limited dataset is available it is hard to train a machine learning model and generalize its applicability to other similar problem. The developed model, in this case, is only applicable for the few data it was trained on.
Because machine learning methods rely solely only on data and the human expertise or judgment is not taken in consideration, it is the data that dictate if the machine learning method will fail or succeed to perform the task it was designed for. The way a machine learning approach works is that a modeler develops a learning algorithm. Then the modeler feeds the learning algorithm with the data and information.
The algorithm learns by itself from the data with no guidance or human interference. It is the algorithm that builds the system. If the data provided for the algorithm is of poor quality and biased then the system is also of poor quality and biased. Hence, cleaning and acquiring the right data to solve a problem with machine learning problem is very crucial. If the data are biases and noisy it is better to stick with a traditional method. Otherwise, the machine learning method will memorize the noise and provide inaccurate results.
Genre: Non-Fiction > Tech & Devices
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