Tech Stack Recommendations for Face Recognition

Determining the architecture is a significant stage for production driven purposes. Herein, a facial recognition pipeline comes with wide product … More

Deep Face Recognition with Redis

Key value databases come with a high speed and performance where we mostly cannot reach in relational databases. Herein similar … More

Deep Face Recognition with Relational Databases and SQL

A face recognition task requires to store multidimensional array and make calculations over it. This task is not mostly matching … More

Deep Face Recognition with Hadoop and Spark

Large scale face recognition is always a challenging task. Nowadays, hadoop based approaches become a de-facto standard for solutions. This … More

Deep Face Recognition with Cassandra

We mostly need the power of map reduce of no sql databases when the data becomes really big and massive. … More

Deep Face Recognition with mongoDB

Face recognition is mainly based on similarity search on facial embeddings. Researches mostly focus on storing vector representations on memory. … More

Feature Importance in Logistic Regression for Machine Learning Interpretability

Feature importance is a common way to make interpretable machine learning models and also explain existing models. That enables to … More

Designing Recursive Functions with Python Multiprocessing

Multiprocessing is a must to develop high scalable products. However, python multiprocessing module is mostly problematic when it is compared … More

Deep Face Recognition with ArcFace in Keras and Python

ArcFace is developed by the researchers of Imperial College London. It is a module of InsightFace face analysis toolbox. The … More

A Gentle Introduction to ROC Curve and AUC in Machine Learning

Model evaluation is very important stage of a machine learning pipeline to understand the robustness. Herein, ROC Curves and AUC … More