Juicy quote (could i modify the problem to: predict a single scalar outcome of #of likes based on a single feature, average colour?):

Part 1 (this article): Linear regression with Tensorflow for single feature single outcome model

Part 2: Tensorflow training illustrated in diagrams/code, and exploring training variations

Part 3: Matrices and multi-feature linear regression with Tensorflow

Part 4: Logistic regression with Tensorflow


We are going to solve an overly simple, and unrealistic problem, which has the upside of making understanding the concepts of ML and TF easy. We want to predict a single scalar outcome, house price (in $) based on a single feature, house size (in square meters, sqm). This eradicates the need to handle multi-dimensional data, enabling us to focus solely on defining a model, implementing, and training it in TF.