MeatScan 2025
Flutter + TensorFlow Lite app for meat freshness detection. Offline AI inference on device for pork, beef, and fish classification.
Flutter TFLite Computer Vision Offline AI
Open to collaboration · AI · Backend · Education
Nguyen Huu Tai
Mobile & Backend Developer | Applied AI Learner
6+ years building cross-platform Flutter apps and Node.js/NestJS backends — now learning Applied AI, image processing, and machine learning. Sharing knowledge on Học AI Cùng Tài!
Ho Chi Minh City, Vietnam
YouTube Channel
About
From mobile & backend to Applied AI
Building reliable products today while deepening expertise in machine learning tomorrow.
I'm a software engineer with over six years of experience delivering production systems — from Flutter cross-platform apps to Express and NestJS backends with REST APIs, MongoDB, Redis, and Linux deployment (Docker, Nginx).
I'm actively transitioning into Applied AI: image processing, image retrieval, on-device inference with TensorFlow Lite, and classical ML foundations through my Vietnamese YouTube course series Machine Learning Cơ Bản.
I enjoy clean architecture, measurable outcomes, and teaching concepts clearly — whether in code reviews, internal tools, or educational content.
Experience
Professional journey
- Current
NestJS Backend Developer
Viet Nam Golden Lotus MTV Co., Ltd
- Internal Asset Costing Module (NestJS): track product sample lifecycle from inventory checkout to return
- Cost allocation & depreciation engine: automatic internal chargebacks and penalty fees by asset condition and usage duration
- Ecommerce platform backend (NestJS): currently contributing to catalog, order, and inventory services
-
Node.js Backend Developer
CITIGYM Development and Investment Services JSC
- REST APIs with MongoDB & Redis for gym operations and membership flows
- Server deployment on Linux with PM2 and Nginx
- Restaurant booking backend: reservations and scheduling for member dining
- Integrations for membership, internal workflows, and cross-service business logic
-
Flutter Developer
Bach Khoa Investment & Development of Solar Energy Corporation
- SSOC Cloud — energy monitoring application
- MS Service — maintenance task management app
- Build and release to Google Play and App Store
-
Flutter Developer
Dien Quang Joint Stock Company
- Dien Quang Smart — smart home app with ZigBee SDK for TV Box communication
- IoT device integration and app performance / UI optimization
-
Tester
TMA Solutions
- Manual and automated test cases for enterprise software
- Bug tracking and quality assurance workflows
- Foundation in software delivery lifecycle
Projects
Selected work
Production apps, AI demos, and educational content.
FlashFlow
Flutter vocabulary app for domain-specific terms — build personalized decks, add self-explanations in simple English, import Excel to generate timed quizzes, and share sets with colleagues via QR code.
Flutter Education Productivity iOS Android
Internal Task & Inventory App
Flutter mobile client with Node.js backend for shift tracking, image check-in, and admin reporting dashboards.
Flutter Node.js MongoDB REST API
ML Course — Machine Learning Cơ Bản
YouTube series from zero to Linear Regression, Logistic Regression, Softmax, Neural Networks, Keras, and MNIST — in Vietnamese.
Education Scikit-learn Keras YouTube
Image Similarity Search
DINOv2 embeddings + FAISS vector search with FastAPI backend and Flutter Web UI. Dockerized deployment.
DINOv2 FAISS FastAPI Flutter Web
OAuth2 Authorization Server
Node.js authorization server with oauth2-server: session management, authorize/token/login flows for third-party apps.
Node.js OAuth2 Sessions Security
YouTube
Machine Learning Cơ Bản
Free Vietnamese course from zero to Neural Networks — 25 lessons across 6 chapters.
Ch.0
Chương 0: Machine Learning là gì? – Lộ trình học từ con số 0!
Chương 0: Machine Learning là gì?
IntroductionRoadmap
Watch on YouTubeCh.1
Chương 1.1: Phân biệt Supervised Learning với Unsupervised Learning
Chương 1: Supervised vs Unsupervised, ML Pipeline, Code Pipeline
SupervisedPipelineColab
Watch on YouTubeCh.1
Chương 1.2: Pipeline cơ bản trong một bài toán Machine Learning
Chương 1: Supervised vs Unsupervised, ML Pipeline, Code Pipeline
SupervisedPipelineColab
Watch on YouTubeCh.1
Chương 1.3 (Code): Code Pipeline Machine Learning Cơ Bản + Chạy trên Google Colab & VS Code
Chương 1: Supervised vs Unsupervised, ML Pipeline, Code Pipeline
SupervisedPipelineColabCode
Watch on YouTubeCh.2
Chương 2.1: Hồi quy tuyến tính - Linear Regression
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.2 (Optional): Ôn lại Đại Số Tuyến Tính Cơ Bản | Ma Trận & Vector
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.3 (Code): Numpy với Ma Trận & Vector
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.4: Mean Squared Error (MSE) – Hàm Loss phổ biến trong Hồi quy tuyến tính
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.5 (Optional): Ôn Tập Hàm Số, Đạo Hàm & Gradient
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.6.1: Giới thiệu Thuật Toán Gradient Descent – Tối ưu hóa mô hình
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.6.2 (Code): Cài đặt Gradient Descent & Momentum
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.6.3 (Code): Cài đặt thuật toán Gradient Descent cho Linear Regression
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.6.4 (Code): Cài đặt Gradient Descent sử dụng vector hóa (ma trận hóa)
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.7 (Code): Hồi quy đa thức (Polynomial Regression) và cách cài đặt
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.8 (Code): Giải pháp Closed-Form
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.9 (Demo): Underfitting và Overfitting
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.2
Chương 2.10 (Code): Linear Regression, Ridge và Lasso trong thư viện Scikit-learn
Chương 2: Linear Regression, MSE, Gradient Descent, Polynomial, Ridge/Lasso
Linear RegressionMSEGradient DescentRegularization
Watch on YouTubeCh.3
Chương 3.1: Logistic Regression – Hồi quy Logistic
Chương 3: Logistic Regression
ClassificationLogistic
Watch on YouTubeCh.3
Chương 3.2 (Code): Cài đặt Logistic Regression với Gradient Descent & scikit-learn
Chương 3: Logistic Regression
ClassificationLogisticCodeGradient Descent
Watch on YouTubeCh.4
Chương 4.1: Mô hình Softmax Regression
Chương 4: Softmax Regression
Multi-classSoftmax
Watch on YouTubeCh.4
Chương 4.2 (Code): Cài Đặt Mô Hình Softmax Regression
Chương 4: Softmax Regression
Multi-classSoftmaxCode
Watch on YouTubeCh.5
Chương 5.1: Neural Network – Mạng Nơ-ron Cơ Bản
Chương 5: Neural Network, Keras MNIST, Roadmap
Neural NetworkKerasMNISTRoadmap
Watch on YouTubeCh.5
Chương 5.2 (Code) : Cài đặt Neural Network với Keras và MNIST
Chương 5: Neural Network, Keras MNIST, Roadmap
Neural NetworkKerasMNISTRoadmap
Watch on YouTubeCh.5
Chương 5.3: Tổng kết chương 1–5 & Gợi ý lộ trình học tiếp (Roadmap)
Chương 5: Neural Network, Keras MNIST, Roadmap
Neural NetworkKerasMNISTRoadmap
Watch on YouTubeSkills
Tech stack
Machine Learning & AI 1 year
Backend Development 2 years
Mobile Development 3 years
Mobile
- Flutter
- Dart
- BLoC
- Riverpod
- Provider
- SQLite
- Hive
- ObjectBox
- Firebase
- Sentry
Backend
- Node.js
- NestJS
- REST API
- WebSocket
- JWT
- OAuth2
- RabbitMQ
- Kafka
Database & DevOps
- MongoDB
- MySQL
- PostgreSQL
- Redis
- Sequelize
- Mongoose
- PM2
- Nginx
- Linux
AI / ML
- PyTorch
- TensorFlow
- CNN
- Image Classification
- Image Retrieval
- Scikit-learn
- Pandas
- NumPy
- Matplotlib
Research interests
Exploring the brain-inspired frontier
Topics I'm reading and experimenting with beyond day-to-day product work.
Spiking Neural Networks
Exploring event-driven, energy-efficient neural models inspired by biological spiking dynamics for future edge AI systems.
Continual Learning
Studying how models acquire new tasks over time without erasing prior knowledge — critical for real-world deployment.
Catastrophic Forgetting
Investigating why neural networks abruptly lose performance on old tasks when trained on new data, and mitigation strategies.
Sleep Replay & Biologically Inspired Learning
Reading on memory consolidation, replay mechanisms, and neuroscience-inspired training loops for more robust learning.
Contact
Let's build something meaningful
Reach out for collaboration on AI applications, backend systems, or ML education content.
- nhtai7071@gmail.com
- Location
- Ho Chi Minh City, Vietnam