Machine Learning Data Science

NGUYEN PHUONG HONG NHA

Tan Binh District, Ho Chi Minh City, Vietnam

091*-***-*** ***********@*****.***

Ho Chi Minh University of Foreign Languages and Informatics (HUFLIT) 2021 - Now Top 10 startup contests organized by HUB 15/09/2024 - 27/10/2024 Excellent Student Scholarship 2023 - 2024

Scientific research students of the Faculty of IT 05/2024 - 07/2024 HUFLIT Excellent Student Scholarship 30% effort 2021 - 2022

EyeCode Company 10/ 2024 - 02/2025

Software to identify objects in traffic - Python 12/ 2023 - 03/ 2024

Predicting heart disease - Python 09/2023 - 11/2023 SUMMARY

I'm a four-year student with a major in Data Science with the skills of data analysis and building algorithmic models using machine learning tools is quite strong, with a foundation in deploying and training AI models, along with an interest in Machine Learning Operations. I have explored model deployment, automation, and optimization using cloud services and CI/CD pipelines. Eager to apply my knowledge to real-world projects, I aspire to become a skilled AI Engineer, collaborating with teams to develop efficient and impactful AI solutions. EDUCATION

Information Technology

GPA: 3.59/4.0

ACHIEVEMENTS

WORK EXPERIENCE

AI Engineer

- Collected and preprocessed data: Gathered data from users, cleaned, and transformed it into a structured format suitable for model training.

- Trained the model: Developed and trained machine learning models using frameworks such as PyTorch and TensorFlow.

- Converted and optimized the model: Transformed the trained model into formats such as ONNX or TensorRT to enhance inference speed.

- Developed and deployed the API: Created RESTful APIs using Flask or FastAPI to serve model predictions.

- Monitored and maintained the system: Tracked model performance in production, identified bottlenecks, and updated models when necessary.

PROJECTS

- Team size: 4

- Position: Leader

- Responsibility: Coordinated a team of 4 to complete a project quite successfully. Collected image data suitable for the topic: cars with more than 300 image data. These images only include 1 or 2 subjects. Used data to divide into 3 sets of train, test and valid. Used 6 models - responsible for processing CNN, resnet50 model included in deep learning. Used software to locate photos when assigning data labels.

- Technical: Using Roboflow software to locate objects in photos, used the Python language is done on Google Colab and Pytorch.

- Achievement: Through the training of basic deep learning models, with the result of the CNN model being the model with 88% achieved. Further analysis of the Transfer learning with feature extraction model, optimized the

% of the model, increased the training efficiency by 7%. Categorized objects and data labels.

- Team size: 3

https://www.linkedin.com/in/nha-nguyen-phuong-hong- 180816324/

Language English ( Toeic: 675), Vietnamese (Native) Computer SQL, Python, Excel, Orange, Hadoop, PowerPoint, Figma, Postman Expertise Problem Solving, Teamwork skill, Web Scraping, Data Collection, Data Cleaning, Data Visualization, Consulting.

- Position: Leader

- Responsibility: Coordinated a team of 3 to complete a project quite successfully. Analyzed, processed, and visualized heart disease data. Used the results to train machine learning models iclude : KNN, Random-forest and find the most accurate training model and drew model conclusions that are highly effective in health diagnostics.

- Technical: Used the Python language is done on Google Colab.

- Achievement: Achieved 95% of the best model predictions were Random-forest model. SKILLS

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