{"id":9,"date":"2026-02-25T02:55:50","date_gmt":"2026-02-25T02:55:50","guid":{"rendered":"https:\/\/techinsightlab.site\/?page_id=9"},"modified":"2026-02-25T02:55:50","modified_gmt":"2026-02-25T02:55:50","slug":"trang-chu","status":"publish","type":"page","link":"https:\/\/techinsightlab.site\/","title":{"rendered":"Trang ch\u1ee7"},"content":{"rendered":"\n\n
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\n \ud83e\uddea AI \u00b7 Machine Learning \u00b7 Data Science \u00b7 Research<\/span>\n

Ph\u00f2ng Lab C\u00f4ng Ngh\u1ec7
AI & Machine Learning<\/span>
H\u00e0ng \u0110\u1ea7u Vi\u1ec7t Nam<\/h1>\n

Nghi\u00ean c\u1ee9u \u1ee9ng d\u1ee5ng AI, Machine Learning v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u \u2014 bi\u1ebfn c\u00f4ng ngh\u1ec7 ph\u1ee9c t\u1ea1p th\u00e0nh ki\u1ebfn th\u1ee9c th\u1ef1c ti\u1ec5n d\u00e0nh cho c\u1ed9ng \u0111\u1ed3ng tech Vi\u1ec7t Nam.<\/p>\n

\n \ud83d\udd2c V\u00e0o Lab Ngay<\/a>\n V\u1ec1 TechInsight Lab<\/a>\n <\/div>\n
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400+<\/strong>Experiments<\/span><\/div>\n
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80+<\/strong>AI Models<\/span><\/div>\n
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100K+<\/strong>Researchers<\/span><\/div>\n
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Weekly<\/strong>Lab Updates<\/span><\/div>\n <\/div>\n <\/div>\n\n
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\n <\/span>\n <\/span>\n <\/span>\n <\/div>\n techinsightlab ~ model_train.py<\/span>\n <\/div>\n
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\n \u276f<\/span>\n python train_model.py<\/span>\n <\/div>\n
Loading dataset… \u2713 2.4M samples<\/span><\/div>\n
Initializing model… Transformer-XL<\/span><\/div>\n
\n Epoch<\/span>\n [<\/span>\n \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2591\u2591\u2591\u2591<\/span>\n ] <\/span>\n 82%<\/span>\n <\/div>\n
Loss: 0.0234<\/span>  Accuracy: 96.8%<\/span><\/div>\n
ETA: 2m 14s<\/span> remaining<\/div>\n
\n \u276f<\/span>\n model.evaluate(test_set)<\/span>\n <\/div>\n
\n \u2192 <\/span>\n F1-Score: 0.968  AUC: 0.991 \u2713<\/span>\n <\/div>\n
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\n \ud83e\udde0<\/span>\n
Model Accuracy<\/strong>96.8%<\/small><\/div>\n <\/div>\n
\n \u26a1<\/span>\n
GPU Cluster<\/strong>Active<\/small><\/div>\n <\/div>\n
\n \ud83d\udcca<\/span>\n
2.4M<\/strong>Samples<\/small><\/div>\n <\/div>\n <\/div>\n\n <\/div>\n<\/section>\n\n\n
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\n \u26a1 N\u0103ng L\u1ef1c Lab<\/span>\n

T\u1ea1i Sao Ch\u1ecdn TechInsight Lab?<\/span><\/h2>\n

Ph\u00f2ng lab c\u00f4ng ngh\u1ec7 to\u00e0n di\u1ec7n \u2014 t\u1eeb nghi\u00ean c\u1ee9u AI \u0111\u1ebfn tri\u1ec3n khai th\u1ef1c t\u1ebf<\/p>\n <\/div>\n

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\ud83e\udd16<\/div>\n

AI & Deep Learning<\/h3>\n

Nghi\u00ean c\u1ee9u v\u00e0 tri\u1ec3n khai c\u00e1c m\u00f4 h\u00ecnh AI ti\u00ean ti\u1ebfn: LLM, Computer Vision, NLP \u2014 t\u1eeb architecture design \u0111\u1ebfn fine-tuning th\u1ef1c t\u1ebf.<\/p>\n <\/div>\n

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\ud83d\udcca<\/div>\n

Machine Learning<\/h3>\n

Ph\u00e2n t\u00edch d\u1eef li\u1ec7u chuy\u00ean s\u00e2u, feature engineering, model selection v\u00e0 \u0111\u00e1nh gi\u00e1 hi\u1ec7u su\u1ea5t theo ti\u00eau chu\u1ea9n h\u1ecdc thu\u1eadt v\u00e0 c\u00f4ng nghi\u1ec7p.<\/p>\n <\/div>\n

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\ud83d\udd2c<\/div>\n

Research & Experiments<\/h3>\n

T\u00e1i hi\u1ec7n c\u00e1c paper n\u1ed5i ti\u1ebfng, th\u1eed nghi\u1ec7m hypothesis v\u00e0 chia s\u1ebb k\u1ebft qu\u1ea3 th\u1ef1c nghi\u1ec7m m\u1ed9t c\u00e1ch minh b\u1ea1ch v\u1edbi c\u1ed9ng \u0111\u1ed3ng.<\/p>\n <\/div>\n

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\ud83d\udee0\ufe0f<\/div>\n

MLOps & Deployment<\/h3>\n

H\u01b0\u1edbng d\u1eabn \u0111\u01b0a model t\u1eeb notebook ra production: containerization, model serving, monitoring v\u00e0 CI\/CD cho ML pipeline.<\/p>\n <\/div>\n

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\ud83d\udcc8<\/div>\n

Data Analytics<\/h3>\n

EDA, visualization, statistical analysis v\u00e0 business intelligence \u2014 bi\u1ebfn raw data th\u00e0nh insights c\u00f3 gi\u00e1 tr\u1ecb th\u1ef1c ti\u1ec5n.<\/p>\n <\/div>\n

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\ud83c\udf10<\/div>\n

Open Source<\/h3>\n

To\u00e0n b\u1ed9 code, notebooks v\u00e0 datasets \u0111\u1ec1u \u0111\u01b0\u1ee3c public tr\u00ean GitHub \u2014 c\u1ed9ng \u0111\u1ed3ng c\u00f3 th\u1ec3 reproduce, contribute v\u00e0 m\u1edf r\u1ed9ng.<\/p>\n <\/div>\n <\/div>\n <\/div>\n<\/section>\n\n\n

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\n \ud83e\uddea<\/span>\n
\n Lab Environment<\/strong>\n TechInsight Lab v2.1<\/small>\n <\/div>\n \u25cf Running<\/span>\n <\/div>\n
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\n CPU Usage<\/span>\n
<\/div><\/div>\n 72%<\/span>\n <\/div>\n
\n GPU Memory<\/span>\n
<\/div><\/div>\n 88%<\/span>\n <\/div>\n
\n RAM<\/span>\n
<\/div><\/div>\n 55%<\/span>\n <\/div>\n
\n Storage<\/span>\n
<\/div><\/div>\n 43%<\/span>\n <\/div>\n <\/div>\n
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\n <\/span>\n LLM Fine-tuning<\/span>\n Running<\/span>\n <\/div>\n
\n <\/span>\n CV Object Detection<\/span>\n Done \u2713<\/span>\n <\/div>\n
\n <\/span>\n Time Series Forecast<\/span>\n Queue<\/span>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n\n
\n \ud83c\udfdb\ufe0f V\u1ec1 Ch\u00fang T\u00f4i<\/span>\n

Nghi\u00ean C\u1ee9u Th\u1eadt,
K\u1ebft Qu\u1ea3 Th\u1eadt<\/span><\/h2>\n

TechInsight Lab \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng b\u1edfi nh\u1eefng k\u1ef9 s\u01b0 AI v\u00e0 nh\u00e0 nghi\u00ean c\u1ee9u tin r\u1eb1ng ki\u1ebfn th\u1ee9c c\u00f4ng ngh\u1ec7 ti\u00ean ti\u1ebfn ph\u1ea3i \u0111\u01b0\u1ee3c lan t\u1ecfa b\u1eb1ng ti\u1ebfng Vi\u1ec7t \u2014 kh\u00f4ng r\u00e0o c\u1ea3n, kh\u00f4ng paywall, kh\u00f4ng oversimplification.<\/p>\n

Ch\u00fang t\u00f4i kh\u00f4ng ch\u1ec9 vi\u1ebft v\u1ec1 AI \u2014 ch\u00fang t\u00f4i th\u1ef1c s\u1ef1 ch\u1ea1y experiments, \u0111\u1ecdc papers, reproduce k\u1ebft qu\u1ea3 v\u00e0 chia s\u1ebb m\u1ecdi th\u1ee9 m\u1ed9t c\u00e1ch minh b\u1ea1ch v\u1edbi c\u1ed9ng \u0111\u1ed3ng developer v\u00e0 researcher Vi\u1ec7t Nam.<\/p>\n

\n Python<\/span>\n PyTorch<\/span>\n TensorFlow<\/span>\n HuggingFace<\/span>\n CUDA<\/span>\n MLflow<\/span>\n Docker<\/span>\n Kubernetes<\/span>\n <\/div>\n
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2021<\/strong>Ra m\u1eaft<\/span><\/div>\n
400+<\/strong>Experiments<\/span><\/div>\n
100K+<\/strong>Readers<\/span><\/div>\n <\/div>\n <\/div>\n\n <\/div>\n <\/div>\n<\/section>\n\n\n
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\n \ud83d\udcc4 Lab Reports & Blog<\/span>\n

B\u00e0i Vi\u1ebft M\u1edbi Nh\u1ea5t<\/span><\/h2>\n

Experiments, tutorials v\u00e0 research reports \u0111\u01b0\u1ee3c c\u1eadp nh\u1eadt h\u00e0ng tu\u1ea7n<\/p>\n <\/div>\n

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\ud83e\udd16<\/span><\/div>\n Deep Learning<\/span>\n <\/div>\n
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\n 24 Th\u00e1ng 2, 2026<\/span>\n \u23f1 18 ph\u00fat<\/span>\n \ud83d\udd2c Experiment<\/span>\n <\/div>\n

Fine-tuning LLaMA 3 Cho Ti\u1ebfng Vi\u1ec7t: Experiment Report & K\u1ebft Qu\u1ea3 Th\ufffd\ufffd\ufffdc T\u1ebf<\/h3>\n

Ch\u00fang t\u00f4i \u0111\u00e3 fine-tune LLaMA 3 v\u1edbi 500K c\u00e2u ti\u1ebfng Vi\u1ec7t v\u00e0 \u0111o \u0111\u1ea1c k\u1ebft qu\u1ea3 m\u1ed9t c\u00e1ch nghi\u00eam t\u00fac. F1-Score \u0111\u1ea1t 96.8%, BLEU score 0.84. To\u00e0n b\u1ed9 code, dataset v\u00e0 weights \u0111\u01b0\u1ee3c public…<\/p>\n

\n LLaMA 3<\/span>\n Fine-tuning<\/span>\n Vietnamese NLP<\/span>\n <\/div>\n \u0110\u1ecdc Lab Report \u2192<\/span><\/a>\n <\/div>\n <\/div>\n <\/div>\n
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\ud83d\udc41\ufe0f<\/span><\/div>\n
\n Computer Vision<\/span>\n

YOLOv10 vs RT-DETR: So S\u00e1nh Th\u1ef1c Nghi\u1ec7m Tr\u00ean Custom Dataset<\/h4>\n 20 Th\u00e1ng 2, 2026<\/span>\n <\/div>\n <\/div>\n
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\ud83d\udcc8<\/span><\/div>\n
\n Time Series<\/span>\n

Temporal Fusion Transformer: D\u1ef1 B\u00e1o Chu\u1ed7i Th\u1eddi Gian V\u1edbi 94% Accuracy<\/h4>\n 18 Th\u00e1ng 2, 2026<\/span>\n <\/div>\n <\/div>\n
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\ud83d\udee0\ufe0f<\/span><\/div>\n
\n MLOps<\/span>\n

Deploy ML Model L\u00ean Production V\u1edbi FastAPI + Docker + K8s<\/h4>\n 15 Th\u00e1ng 2, 2026<\/span>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
\n Xem T\u1ea5t C\u1ea3 Lab Reports<\/a>\n <\/div>\n <\/div>\n<\/section>\n\n\n
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\n \ud83d\udcac C\u1ed9ng \u0110\u1ed3ng<\/span>\n

Researcher N\u00f3i G\u00ec V\u1ec1 TechInsight Lab?<\/span><\/h2>\n <\/div>\n
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\u2605\u2605\u2605\u2605\u2605<\/div>\n

“TechInsight Lab l\u00e0 ngu\u1ed3n h\u1ecdc AI ti\u1ebfng Vi\u1ec7t duy nh\u1ea5t t\u00f4i th\u1ea5y \u0111\u1ee7 s\u00e2u \u0111\u1ec3 \u00e1p d\u1ee5ng v\u00e0o c\u00f4ng vi\u1ec7c th\u1ef1c t\u1ebf. C\u00e1c experiment report minh b\u1ea1ch, c\u00f3 code, c\u00f3 s\u1ed1 li\u1ec7u \u2014 kh\u00f4ng ph\u1ea3i content marketing.”<\/p>\n

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QL<\/div>\n
Qu\u1ed1c L\u00e2m<\/strong>ML Engineer \u00b7 H\u00e0 N\u1ed9i<\/span><\/div>\n <\/div>\n <\/div>\n
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\u2605\u2605\u2605\u2605\u2605<\/div>\n

“Series MLOps c\u1ee7a TechInsight Lab \u0111\u00e3 gi\u00fap team t\u00f4i tri\u1ec3n khai production pipeline \u0111\u1ea7u ti\u00ean th\u00e0nh c\u00f4ng. H\u01b0\u1edbng d\u1eabn chi ti\u1ebft t\u1eebng b\u01b0\u1edbc, code ch\u1ea1y \u0111\u01b0\u1ee3c ngay \u2014 ti\u1ebft ki\u1ec7m cho t\u00f4i h\u00e0ng tu\u1ea7n research!”<\/p>\n

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HY<\/div>\n
H\u01b0\u01a1ng Y\u1ebfn<\/strong>Data Scientist \u00b7 TP. HCM<\/span><\/div>\n <\/div>\n <\/div>\n
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\u2605\u2605\u2605\u2605\u2605<\/div>\n

“L\u00e0 sinh vi\u00ean n\u0103m cu\u1ed1i ng\u00e0nh CNTT, TechInsight Lab cho t\u00f4i c\u00e1i nh\u00ecn th\u1ef1c t\u1ebf v\u1ec1 AI m\u00e0 tr\u01b0\u1eddng \u0111\u1ea1i h\u1ecdc kh\u00f4ng d\u1ea1y. Reproduce \u0111\u01b0\u1ee3c paper c\u1ee7a h\u1ecd l\u00e0 b\u01b0\u1edbc ngo\u1eb7t l\u1edbn trong career c\u1ee7a t\u00f4i.”<\/p>\n

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TT<\/div>\n
Tu\u1ea5n Th\u00e0nh<\/strong>AI Researcher \u00b7 \u0110\u00e0 N\u1eb5ng<\/span><\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/section>\n\n\n
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<\/div>\n \ud83d\ude80 Tham Gia Lab<\/span>\n

C\u00f9ng Nhau Kh\u00e1m Ph\u00e1
Bi\u00ean Gi\u1edbi C\u1ee7a AI<\/span><\/h2>\n

Tham gia c\u00f9ng 100.000+ researcher v\u00e0 engineer \u0111ang theo d\u00f5i TechInsight Lab. Nh\u1eadn lab reports, experiment updates v\u00e0 tutorials m\u1ed7i tu\u1ea7n \u2014 ho\u00e0n to\u00e0n mi\u1ec5n ph\u00ed.<\/p>\n

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