Almost everyone wants to jump head first into machine learning without learning data preprocessing, which is the non-sexy part.
Well …
Summary: In all previous articles, given some features, such as ‘house size’, we used Tensorflow (TF) to perform linear regression to predict the outcome, such as ‘house price’, which is a numeric value. We will now look at logistic…
Summary: With concepts of single-feature linear-regression, cost function, gradient descent (from Part 1), epoch, learn-rate, gradient descent variation (from Part 2) under our belt, we are ready to…
Summary: We show in illustrations how the machine learning ‘training’ process happens in Tensorflow, and tie them back to the Tensorflow code. This paves the way for discussing ‘training’ variations, namely stochastic/mini-batch/batch, and adaptive learning rate…
Summary: Tensorflow (TF) is Google’s attempt to put the power of Deep Learning into the hands of developers around the world. It comes with a beginner & an advanced tutorial, as well as a course on Udacity. However, the materials attempt to introduce both ML and…