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Neural Networks Fundamentals using TensorFlow course contents
The Neural Networks Fundamentals TensorFlow course in Chicago will initiate with TensorFlow intro such as creation, preloading, reading, restoring the variable, TensorFlow mechanics, re-establishing the factors, and also foundation of TensorFlow and on how to imagine and assess models, for example placeholders, inputs, assembling the charts, paired and record grouping and confinements of the recognition, preparing and assessing the models, learning calculations, from observation to Support vector machines, nonlinear decision limits, prologue to Artificial Neural Networks, Feedforward as well as feedback Neural Networks, Convolutional Neural Networks and their main objectives and model engineering in addition to standards, more on code associations and propelling in addition to preparing the model, forward and back spread, multilayer discernments, limiting the cost work, case study as well as an assignment.
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