The purpose of this document is to present the linear classification algorithm SVM. The development of this concept has been … More

# Author: Alexis Alulema

# DDD Clean Architecture Template

(GitHub Repo: https://github.com/alulema/DDD-CleanArchitectureTemplate) These last 10 months I’ve been delighted working with ASP.NET Core, considering the improvements made by Microsoft … More

# C# Sudoku Solver

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

# 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 … More

# 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 … More

# 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 … More

# 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 … More

# 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 … More

# Loss Functions (Part 1)

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

# Activation Functions in TensorFlow

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