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Deep Forward Neural Network In Python use Tensorflow to build a deep forward deep learning architecture using the sequential model. The problem with such a long network is finding the correct hyperparameters that will make it work. So many dense layers have the potential problem of confusing our network and it won't be able to make good predictions. The trick to finding the right architecture is setting up an experiment. In the form of a loop in Python and iterating thro

Feed Forward Neural Network In Python using Tensorflow design a Feed Forward neural network to predict a regression problem with 40 features. To stick to the style of a Feed Forward architecture we continue with 40 neurons down our Dense or fully connected layers. Although adding in more Dense layers will help at first the comes a point we more Dense layers won't help with the problem any further . A good way to look at this is your dataset has only a certain number of hig

The perceptron model was the first and simplest type of neural network developed back in 1943. It works well but is certainly far from as powerful as modern neural networks with advanced layers such as the recurrent layer , convolutional layer , or customer layers. In Python using Tensorflow with the sequential API the the build a neural network in the style of a perceptron .   Data Science Teacher Brandyn YouTube Channel One on one time with Data Science Teacher Brandyn Fo