oleksandr-g-rock Goto Github PK

followers: 5.0 following: 16.0 repos: 25.0 gists: 4.0

Name: Oleksandr G.

Type: User

Bio: Senior DevOps engineer

Location: UK

Blog: https://oleksandrg.medium.com/

Hi 🌍, I'm Oleksandr G.

Senior DevOps Engineer

I write insightful and informative articles on DevOps, technology trends, and software practices. Check out my work on Medium.

📧 Reach me at: [email protected]

🛠️ Technologies & Tools

👨‍💻 Programming Languages

💻 Operating Systems

🔗 Networking

🗃️ Databases

📦 CI/CD & Configuration Management

☁️ Cloud Platforms

📊 Monitoring & Logging

🔬 Artificial Intelligence & Data Science

🚀 Projects & Accomplishments

CI/CD Solutions Improvement: Developed a custom Blue-Green deployment strategy, migrated to cloud runners, and created custom solutions for quick rollback deployments, enhancing production stability and reducing costs.
Cloud Environment Optimization: Implemented custom tuning for Kubernetes clusters and managed cloud resources, resulting in substantial cost savings.
Process Optimization Expert: Streamlined numerous processes through automation and best practices, significantly enhancing operational efficiency.
Leadership & Mentorship: Led and mentored a DevOps team, fostering professional growth and enhancing team success.
AI & Data Science Initiatives: Developed and implemented AI-based solutions, improving project interfaces and operational efficiency.

Let's connect and collaborate! 🚀

📈 GitHub Statistics

Oleksandr G.'s Projects

classify_picamera_in_live_time_cusom_model

Image classification (persons, animals, other) on raspberry pi from pi-camera (in live time) used custom model .h5 (output to terminal)

classify_picamera_with_while_cusom_model

Image classification (persons, animals, other) on raspberry pi from pi-camera (with cycle while) used custom model .h5 (output to terminal)

create_animation_graphs_in_python

How to create live animation graphs in python

custom_object_detection_person_notperson

disease-recognition-from-xray

Recognition (3 diseases) from X-ray (Machine Learning tutorial) with accuracy: 96%

flower_classification

Image Classifications: Flowers Recognition

flutter_app

GitHub Action Pipeline for Building and Packaging a Flutter App

how-to-divide-image-4-part-using-opencv

How to divide the image into 4 parts using OpenCV

how_to_convert_h5_model_to_tflite

How to convert h5 model to tflite model

how_to_create-image-classification-for-recognizing-persons-animals-others

Create image classification for recognizing persons, animals, others.

how_to_create_confusion_matrix

How to create a confusion matrix with the test result in your training model & How to visualize the history of network learning: accuracy, loss in graphs.

image_classification_out_to_terminal

Simple image classification on raspberry pi from pi-camera (in live time) used the pre-trained model mobilenet_v1 and TensorFlow Lite (output to terminal)

image_classification_pi_camera_live_time_custom_model_tflite

Image classification (persons, animals, other) on raspberry pi from pi-camera (in live time) used custom model tflite (output to terminal)

image_classify_tflite_camera_pi_while

Image classification (persons, animals, other) on raspberry pi from pi-camera (with cycle while) used custom tflite model (output to terminal)

image_lassify_tflite_simple

Simple image classification (persons, animals, other) on raspberry pi used custom model tflite (output to terminal)

install_packages_for_pi_nn

live-time-used-custom-model-tflite-dividing-image-into-4

oleksandr-g-rock

quantization

Quantization (post-training quantization) your (custom mobilenet_v2) models .h5 or .pb models using TensorFlow Lite 2.4

simple-image-classification-4-divide-image-tflite

Simple image classification (persons, animals, other) on raspberry pi used custom model tflite (output to terminal) dividing image into 4 parts using OpenCV and TensorFlow Lite