Top skills
- Deep Learning
- Machine Learning Infrastructure
- Computer Vision
Main tools
- Pytorch
- Tensorflow
- Docker
- Kubernetes
About
Work history
Freelance Sofware Engineer
Independent contractor with startups
April 2016 - June 2018University of Patras
MEng Electrical and Computer Engineer
September 2012- September 2017Projects and teams
Deep Learning in Production Book
https://amzn.to/3oa50VjDeep Leanrning in Production explores how to develop, deploy and scale Deep Learning pipelines with Tensorflow. The reader will learn: • how to design a deep learning system from scratch • how to structure and develop production-ready machine learning code • how to develop efficient and scalable data pipelines • how to make it available to the public by setting up a service on the cloud • how to scale and maintain the service as the user base grows
- Status: live
- MLOps
- Deep Learning
- Tensorflow
Introduction to Deep Learning and Neural Networks Course
https://www.educative.io/courses/intro-deep-learning/The course provides to the student the basic concepts they need in order to start working with and training various machine learning models. Takeaway Skills: • Understanding of the most popular Deep Learning models • A solid grasp on the mathematics and the intuition behind the algorithms • A good experience with Deep Learning Programming and Pytorch
- Status: live
- Deep Learning
- Pytorch
AI Summer
https://theaisummer.com/I founded AI Summer as a way to document my journey in Machine Learning. Now AI Summer is one of the biggest educational Deep Learning blogs globally with over 40.000 monthly visitors, a newsletter of 3000 emails and almost 100 highly detailed articles. We cover a wide range of topics from Computer Vision and Natural Language Processing to Machine Learning Infrastructure, Medical Imaging and Reinforcement Learning.
- Status: live
- Deep Learning
- Machine Learning
HubSpot - Machine Learning Infrastructure team
• The Machine Learning Infrastructure team is responsible for building and maintaining all Machine Learning services and pipelines inside HubSpot. Handled more than 1 billion requests per day and almost 70 machine learning models on production. • Technologies used: Java, Python, MySQL, HBase, Hadoop, Kafka, AWS, Docker, Kubernetes
- Machine Learning
- MLOps
- Java
Master thesis - Development of computer vision framework with deep learning techniques
https://nemertes.lis.upatras.gr/jspui/handle/10889/10955?mode=fullAs part of my thesis during my MEng degree in Electrical and Computer Engineering , we developed a Computer Vision library that allows the user to recognize objects in images using deep learning. To accomplish that, the user/developer can define his own neural network architecture and train his own images on it. The system supports fully connected and convolutional neural networks , which we implement in C++ from scratch. To speed up the training, we decided use parallelization and execute the training in GPU, which we programmed with the OpenCL library. Also OpenCV was used to parse and read the images and do all the necessary preprocessing of the dataset.
- Deep Learning
- GPU programming
- Computer vision
Eworx SA
• Built the core of a real-time Recommendation Engine with Python using Natural Language processing and Machine Learning techniques for Experly, a travelling web application. • Designed an in-house library for Source Code Analysis for different programming languages. • Implemented data science pipelines for tasks such as spell correction, language detection on different projects for European organizations such as CEDEFOP and Skills Panorama websites.
- R
- Python
- Javascript
European Training Foundation Database
During my time on Eworx SA, I developed a full-stack web application for the European Training Foundation (ETF). The purpose of the app is to store, organize and manipulate their data, perform validations and verifications on them and build reports for internal or external use. The user is able to add, edit or delete data from the browser using an excel-like table, create reports based on selected filters and build interactive visualizations such as Pie Charts, Bar Charts and Maps.
- R
- Javascript
Chill- Meet and Movie Date
Developed and published an Android app with a NoSQL database and a server hosted in Google cloud. The app connects users via common interests in movies and tv shows and it organically grew to more than 500 users within the first two weeks.
- Android
- Java
Differential Wheeled Robot
https://github.com/SergiosKar/-Robotic-vehicleProgrammed an embedded board for a 2 wheeled robot. he robot is able to move to straight line, follow a certain path,such as a trinagle or a circle , detect and avoid obstacles with supersonic sensor.
- Embedded programming
Robot motion plainning
Designed a system for robot navigation on 2D space with C++ and computational geometry techniques, such as voronoi diagrams and visibility graphs.
- Robotics
Simulation of Robotic Arm
https://github.com/SergiosKar/Robotic-ArmStudy of Kinematics, Dynamics, Position, Control and Simulation of robotic arm with MATLAB robotic toolbox
- Robotics