I'm a Advanced ML Engineer with a passion for building robust and scalable applications. Some facts about me:

• 🔭 Student pursuing a Master’s Degree in Electrical Engineering and Information Technologies, specializing in Dedicated Computer Systems
• 👨‍💻 Advanced ML Engineer focusing MLOps.
• 🥅 2024 Goals: To expend my knowledge in Machine Learning, Deep Learning, Federated Learning and Cloud Computing.
• ⚡ Fun fact: I love to experiment and make different kinds of coffee and tea !

• Machine Learning & Deep Learning
• Federated Learning
• Data&MLOps
• Cloud Computing
• Information Security
• AI in Healthcare

• Python
• Javascript
• C

I have hands-on experience with various AWS services, including:

• AWS S3: Scalable object storage for your applications.
• AWS SageMaker: Building, training, and deploying machine learning models.
• AWS Lambda: Running serverless functions in the cloud.
• AWS IAM: Managing access and permissions for your AWS resources.
• AWS DynamoDB: NoSQL database for high-performance applications.
• AWS EC2: Scalable virtual servers in the cloud.
• AWS Elastic Container Service: Orchestrating and managing containerized applications.
• AWS API Gateway: Building and managing APIs for your applications.
• AWS Cognito: Adding authentication and authorization to your applications.
• AWS CloudFormation: Managing and provisioning your AWS infrastructure as code.

Here's a glimpse of the tools and frameworks I work with:

• Docker: Building and deploying applications in containers for easy scalability and portability.
• Pulumi: IaaC that enables to define, deploy and manage cloud infrastructure using programming languages.
• Serverless Framework: Simplifying the deployment and management of serverless applications.
• Flask: My go-to Python framework for building robust and efficient backends.
• jQuery or React: Crafting interactive and responsive frontend experiences.

In the realm of Machine Learning, Deep Learning, Federated Learning, Data Science, Data&MLOps, I leverage various libraries and frameworks:

• Numpy, Scipy, and Pandas: Fundamental libraries for numerical computing and data manipulation.
• Matplotlib, Plotly, and Seaborn: Creating stunning visualizations to gain insights from data.
• Scikit-learn, XGBoost, and LightGBM: Powerful Machine Learning libraries for classification, regression, and more.
• Keras and TensorFlow: Building and training Deep Learning models.
• TensorFlow Federated and Flower: Exploring Federated Learning for Distributed Machine Learning.
• MLflow: Open-source platform for managing and tracking machine learning experiments.
• Hugging Face: Platform for building, training and deploying Machine Learning models
• Langchain (Embedchain): Powerful python libraries for LLMs

I am always eager to expand my knowledge and collaborate on challenging projects. Feel free to reach out to me if you're interested in potential collaborations on the following platforms:

• LinkedIn: Bojan Jakimovski
• Research Gate: Bojan Jakimovski
• Email: [email protected]

Looking forward to connecting with you and exploring exciting opportunities together! 🚀