zaina826 Goto Github PK

followers: 4.0 following: 61.0 repos: 24.0 gists: 0.0

Name: Zaina Abushaban

Type: User

Bio: AI Engineering student skilled in backend (Python, Java, C++) and frontend (JavaScript, HTML, CSS). Currently exploring neural networks.

Blog: www.linkedin.com/in/zaina-abushaban

Hola! I'm Zaina! 🐝

Welcome to my corner of GitHub!

🌟 About Me

I'm Zaina Abushaban, a passionate developer with a keen interest in AI, Machine Learning, and Software Development. I love solving real-world problems using technology and continuously strive to learn and grow in my field.

🎓 Education: Pursuing a Bachelor’s degree in AI Engineering from Hacettepe University.
🌱 Current Focus: researching computer vision, mathematical prediction software, neural networks, and their optimizations.
🔭 Currently Working On: Optimizing neural networks and TinyML projects.
💬 Ask Me About: AI, Machine Learning, Python, Java, C++, and front-end development.
📫 Contact Me: [email protected] | www.linkedin.com/in/zaina-abushaban | Ankara, Turkey | Cairo, Egypt

🚀 Skills

Code & Software Arsenal ⚔️

Languages

English: Native
Arabic: Native
Turkish: Advanced
French: Beginner

🥇 Certifications and Milestones

Full scholarship by the Turkish government to study AI engineering at one of Turkey's top universities.
Granted full scholarship to study and intern at EPFL Switzerland in the Data Analytics Labs.
Participating in a faculty-mentored TinyML research project at Hacettepe DREAM Committee, optimizing computer vision applications for microcontrollers using quantization and pruning.
HUPROG 2024 National Programming Competition Finalist.
Completed a data analysis course from Google.
Maintaining a GPA of 3.5 in my Bachelor’s degree program.
Certificates: codeX, EPFL in Switzerland, CorrelationOne in Jordan, and various local institutions in Turkey and Palestine.
Research: Working on TinyML and neural network optimization.
Leadership: Demonstrated leadership in collaborative projects and developed energy-efficient and optimized technologies.

🔍 What You'll Find in My Repositories

PyTorch and TensorFlow Projects: Including computer vision applications using Python and NumPy.
Machine Learning Projects: Covering various techniques and algorithms:
- Natural Language Processing (NLP): Projects focusing on text classification and sentiment analysis.
- K-Nearest Neighbors (KNN): Implementations for classification and regression tasks.
- Convolutional Neural Networks (CNN): Image classification and recognition projects.
- Regression Models: Linear regression, logistic regression, and other statistical methods.
- Clustering: K-means, hierarchical clustering, and other clustering techniques.
Data Exploration:
- SQL: Projects using SQL for data manipulation and querying.
- Visualizations: Data visualizations using libraries like Matplotlib, Seaborn, and Plotly.
- Python Libraries: Utilizing libraries such as Pandas, NumPy, and SciPy for data analysis and processing.
- Exploring various datasets, including using the Gene Ontology framework to discover relationships between GO terms, proteins, and annotations.
Front-End Projects: My journey began with front-end development using JavaScript, React, and React Native.
University and EPFL Projects: Algorithms and data structures classes, covering topics like dynamic programming, clustering, and regression models.

🌐 Connect with Me

Email: [email protected]
Phone: +90 (552) 680 28 93
Location: Ankara, Turkey
LinkedIn & Resume: Zaina Abushaban
GitHub: zaina826

Zaina Abushaban's Projects

algorithms-sorting-searching-effeciency

Exploring different sorting and searching algorithms using Java, and running them against different types of data and different quantities. Finding attributes and details about each algorithm, and using visualizations to further understand them.

covid-app

App which helps Adults and children learn more about the corona virus and it's recent updates.

cv-constructor

data-preprocessing-and-knn-regrision

Using the the famous housing dataset, this project explores data preprocessing, outlier detection and handling, encoding ordinal features, KNN regression and Linear Regression

dimensionality-reduction-and-clustering

With the "Mall Customers" dataset, we explore K-means and agglomerative clustering, and explore the concept of dimensionality reduction using Principal Component Analysis (PCA)

dynamic-memory-allocation-tetris

Using dynamic memory allocation and matrix mathematics, this game coded with C++ is called block fall, a game environment filled with falling blocks, requiring strategic maneuvering.

eco-friendly-power-grid-optimization

Using dynamic programming and greedy programming, this project tackles populating a power grid to optimize energy usage, and times at which batteries should be recharged. It also uses greedy programming to best utilize Electric Service Vehicles to distribute power and offer aid in emergencies.

high-dimensional-matrices.

Application of matrix data structures to decode images, using convolution, image sharpening, edge detection and gradient calculus.

image-classification-network

Simple image detection neural network, Python implementation, with no additional libraries from scratch. The network aims to classify images into the number they represent, this of course isn't the optimal way, but it is good practice to understand the basics behind neural networks, code is provided along with the dataset, and an explanation PDF.

image-classification-with-tensorflow

Using the Mnist data set, this neural network is able to identify with 99% accuracy the digit shown in the image, this network utilizes Keras and TensorFlow.

image-enhancement

image-enhancement-

knn-classifier-and-logistic-regression

Implementing Data preprocessing, visualization and model building on the Wisconsin Cancer Dataset, We explore KNN classifier and Logistic Regression

leetcode

Some Leetcode Answers

natural-language-processing-

Classification Project using Natural Language Processing in Python

project-vitae-graphs--

Graphs, Connected Components, Minimum Spanning Trees and More. Using Java, we analyze an XML format text, to get information about a specific species and their superhuman genetics, we find unique structures and compare them to human genetic structures. Then we tackle finding molecules for synthesis of molecules used in the serum.

pytorch-tutorial

Following Patrick Loeber Tutorial on Pytorch, Can be found at https://www.youtube.com/playlist?list=PLqnslRFeH2UrcDBWF5mfPGpqQDSta6VK4

quest

Quest is a job and gig-finding platform tailored for Gaza, connecting local job seekers with employers. It's built with JavaScript, React, and React Native, ensuring a seamless experience for users to post and accept job offerings in their city.

queues---computer-networking

Implementing a basic version of network communication between peers within a computer network; that is, to implement a highly simplified computer networking protocol family similar to the Internet protocol suite, using stacks and queues as our base data structure.

smart-city-part-2-optimal-path-map-

Using Topological Sort, Shortest Path, and Regex, we tackle the second part of the smart city challenge. The first task includes using DP or Topological Sort to find an optimal schedule for the tasks. The second includes using optimal path, or Dijkstra's to find optimal paths to get around the city using walking or a train system.