(GitHub Repo: https://github.com/alulema/SudokuSolverNet) I was revisiting a couple of basic AI concepts: Depth First Search and Constraint Propagation, and I…

# TensorFlow High-Level Libraries: TF Estimator

TensorFlow has several high-level libraries allowing us to reduce time modeling all with core code. TF Estimator makes it simple…

# TensorFlow Way for Linear Regression

In my two previous posts, we saw how we can perform Linear Regression using TensorFlow, but I’ve used Linear Least…

# Cholesky Decomposition for Linear Regression with TensorFlow

Although Linear Least Squares Regression is simple and precise, it can be inefficient when matrices get very large. Cholesky decomposition…

# Linear Least Squares Regression with TensorFlow

Linear Least Squares Regression is by far the most widely used regression method, and it is suitable for most cases…

# Classification Loss Functions (Part II)

In my previous post, I mentioned 3 loss functions, which are mostly intended to be used in Regression models. This…

# Loss Functions (Part 1)

Implementing Loss Functions is very important to machine learning algorithms because we can measure the error from the predicted outputs…

# Activation Functions in TensorFlow

Perceptron is a simple algorithm which, given an input vector x of m values (x1, x2, …, xm), outputs either…

# Working with Matrices in TensorFlow

Matrices are the basic elements we use to interchange data through computational graphs. In general terms, a tensor can de…

# Understanding Variables and Placeholders in TensorFlow

Usually, when we start using TensorFlow, it’s very common to think that defining variables is just as trivial as a…