I love ICT and am fascinated by its power to transform ideas into reality. I’m also deeply interested in the people side of technology — fostering collaboration, learning, and team growth.
- 🌟 LinkedIn Profile: Alice I. Telese
- 🤖 Tech Stacks: Django/React.js, SpringBoot 3/React.js
- 💪🏼 Core Strengths: Natural curiosity and eagerness to learn.
- Languages: Python, TypeScript, Java, SQL
- Frameworks: Django, Flask, FastApi, SpringBoot 3
- Packages/Libraries & Tools: Django REST Framework, Django Filter, Django CORS Headers, requests, urllib3, lombok, Spring JPA, Spring Mail
- Caching & Messaging: ActiveMQ Artemis, Redis
- Databases: MySQL, SQLite, MongoDB
- Languages: JavaScript, TypeScript, HTML/CSS
- Frameworks: React.js, Vite, Angular 18+
- Packages & Tools: Tailwind CSS, Material UI
- Languages: Python, Java
- Libraries: scikit-learn, pandas, numpy, sentence-trasformers, tokenizers, torch, transformers, DeepLearning4J, ND4J, smile
- IDEs: Pycharm, IntelliJ Idea, Visual Studio Code
- Version Control: Git/GitHub, BitBucket
- API Testing & Debugging: Postman
- Kanban: Jira
🌥️ Skymet
- Description: Skymet is a full-stack weather app designed to provide real-time weather data with a seamless user experience.
- Goal: To make it public as an educational resource and demonstrate my ability to build end-to-end applications.
Tech stack: Django, DRF, JavaScript/React/Vite, Tailwind CSS, Recharts, OpenWeatherMap API, IP-API
- Description: This is a production-style REST API developed using Java Spring Boot, built as part of my onboarding process in the company. The app might not be completely finished because the focus shifted according to the priorities assigned to me by my senior. The projects
Consumer,commonLibraryandrecommenderare modules and microservices developed to work with this main project. - Goal: To teach myself how to develop in Spring Boot 3.
Tech stack: Java 8+, Spring Boot 3, JMS, Spring Mail, Spring Data, MySQL, RESTful API, lombok.
- Description: This is a machine learning microservice developer for the Library Management System onboarding project. This is my first ML project ever, I knew nothing about ML when I started developing it, and I had lots of fun learning.
- Goal: To select appropriate book recommendations according to user history and collective behaviour.
Tech stack: Python, Django/DRF, scikit-learn, sentence-transformers, BERT embeddings, NLP, DBScan clustering
When I'm not coding, I love:
- 🚶🏻♀️ Long walks in nature
- 🎮 Playing video games
- 🎶 Listening to music
- 🎥 Watching movies and series
- 📚 Reading fantasy books
- 😫 Thinking about more apps to develop
I'm always open to collaborating on exciting projects or discussing ideas.