Design patterns are the best practices in a software engineering but they are mostly missing in machine learning studies. Software … More
Category: Machine Learning
Graph Embeddings in Neo4j with GraphSAGE
Facial recognition, reverse image search or natural language processing are all based on vector embeddings. Graphs are powerful way to … More
A Gentle Introduction to Cypher Queries in Neo4j
Graph databases are very powerful tools to store entities and its relations. Those data stores also offer to reveal some … More
Large Scale Face Recognition with Pinecone Vector Database
A production-driven facial recognition pipeline comes with the common concerns about how to store the vector embeddings. Because vectors are … More
Deep Face Detection with RetinaFace in Python
InsightFace entered to the facial recognition world with two spectacular modules: its face recognition model ArcFace, and its face detection … More
Why Logistic Regression is Linear
A common mistake is to classify logistic regression algorithm as a non-linear machine learning model. In this post, we are … More
Deep Face Recognition with Neo4j
Graph databases come with the power of discovering relations hard to find. Here, Neo4j is a cool graph database. As … More
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
