Machine Learning, Deep Learning, Computer Vision, NLP, RL

Trần Xuân Khánh

Phone Number: ***.****.*** Email: ad5ve4@r.postjobfree.com

Linkedin: https://www.linkedin.com/in/trần-xuân-khánh Github: https://github.com/xuankhanh1907 Education

Ho Chi Minh City University Of Technology – HCMUT VTC-Academy Major: Electronics - Telecommunications Engineering Major: AI Specialist Language

English: Toeic 540

Japanese: N4

Skill

Programming Language: Python

Database Programming Languge: SQL

Framework: OpenCV, Numpy, Pandas, Matplotlib, Pytorch, Tensorflow, Keras, Seaborn, Scikit-Learn. Tool: VS Code, Pycharm, Google Colab.

Knowledge

Data Mining Machine Learning Deep Learning Computer Network Computer Vision NLP Communications Systems Mobile Communications Project

Data Mining: House Price, Weight Regression, Pokemon win percent prediction, UCI-Secom classify, Diabetes prediction, BigMart Sales prediction, Mall Customers Clustering. Task: Missing Data Impution, Imbalanced Data Processing, Noisy & Outlier Processing. Feature Scaling, feature enrichment, feature Reduction. Apply machine learning models like Linear Regression, Polynomial Linear Regression, K-Means, DBSCAN, Mean shift to prediction, classification.

Compute Vision: Fashion Recognition, Traffic Sign Detection, Bin-Picking, Object Detection (bird, bus, truck), Dog vs Cat classification.

Task: Use R-CNNs, AlexNet, LeNet, VGG, GoogleNet, MobileNet to classify, recognize, detect object. Natural Language Processing: Word vector, Vietnamese Sentiment Analysis, Spam Classification. Task: Use Skip-Grams method to create Word embedding. Use RNN languge model to classify VietNamese sentiment in film’s comment. Use BERT model to classify spam messenges, email.

Work Experience

ACT Telecommunications Joint Stock Company (12/2020-06/2023) Position: BTS Technical personnel

Work content: Manage Viettel’s BTS

Tho Nguyen Joint Stock Company (2019)

Position: Technical personnel

Work content: Electric device installation

Sieu Nhat Thanh Ltd (2018)

Position: Technical personnel

Work content: Parabol antenna equipment installation, find the cause of the signal problem and recover.