Face recognition technology is mainly based on face verification. All scenario depends on feeding two face photos to a convolutional neural … More
Author: Sefik Serengil
Fine Tuning The Threshold in Face Recognition
Face recognition models are regular convolutional neural networks. These models are responsible to represent face images as vectors. We’ll find … More
XGBoost vs LightGBM
XGBoost and LightGBM are the most common and most popular gradient boosting frameworks nowadays. There is no absolute better solution … More
Parametric and Non-Parametric Models in Machine Learning
Machine learning algorithms are classified as two distinct groups: parametric and non-parametric. Herein, parametricness is related to pair of model … More
A Gentle Introduction to Face Recognition in Deep Learning
Modern face recognition pipelines consist of 4 common stages. These are detection, alignment, representation and verification. These might be confusing … More
Flask Experiments for a Deep Learning Project
Flask is a pretty web framework to publish python projects as an api. Recently, I’ve published one of my project … More
Feature Importance in Decision Trees
A decision tree is explainable machine learning algorithm all by itself. Beyond its transparency, feature importance is a common way … More
Publishing Python Packages on Pip and PyPI
Library diversity might be the trigger of being popular of python programming language nowadays. This encourages open source culture as … More
A Step by Step CHAID Decision Tree Example
CHAID is the oldest decision tree algorithm in the history. It was raised in 1980 by Gordon V. Kass. Then, … More
Face Alignment for Face Recognition in Python within OpenCV
Face alignment is an early stage of the modern face recognition pipeline. Google declared that face alignment increases the accuracy … More
