In a previous post I talked about how to preprocess and explore image dataset. In this post, I will talk about how to model image data with neural networks having a single neuron, using sigmoid function. Original version of this blog can be found here. This is equivalent to logistic…

Added by Jobil Louis on January 20, 2018 at 5:00pm — No Comments

In this series, I will talk about training a simple neural network on image data. To give a brief overview, neural networks is a kind of supervised learning. By this I mean, the model needs to train on historical data to understand the relationship between input variables and target variables. Once trained, the model can be used to predict target variable on new input data. In the previous posts, we have written about linear, lasso and ridge regression. All those methods come under…

ContinueAdded by Jobil Louis on January 16, 2018 at 8:00pm — No Comments

In the last post, we talked about how to estimate the coefficients or weights of linear regression. We estimated weights which give the minimum error. Essentially it is an optimization problem where we have to find the minimum error(cost) and the corresponding coefficients. In a way, all supervised learning algorithms have optimization at the crux of it where…

ContinueAdded by Jobil Louis on January 2, 2018 at 3:30pm — No Comments

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