(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…
