I’m currently working on Capgemini.
I’m currently learning GNN, LLMs, Efficient and Scalable AI.
I’m looking for something new or creating some project.
I'm also interested in competitive programming.
How to reach me [email protected]
Things I code with
Featured Projects
LBGCN
Master's Thesis:Enhancing Text Classification with LLM-Augmented BertGCN and Advanced Machine Learning Techniques
LLM
Theoretical Framework and Practical Applications of Fine-Tuning
Machine Learning
- 01.ML basic--go through the machine learning process.
- 02.Matrix(derivation & lsm)--performing matrix calculations using NumPy.
- 03.Linear Regression--go through the linear regression process.
- 04.Logistic Regression--go through the logistic regression process.
- 05.Classification model & model evaluation--concepts of classification model decision boundaries & model evaluation.
- 06.Scikit-Learn--use Scikit-Learn to building and evaluating machine learning models.
- 07.Clustering model--clustering models: KMeans and DBSCAN.
- 08.Decision Tree--Decision Trees: ID3 (Iterative Dichotomiser 3), C4.5, & CART.
- 09.bagging & Random Forest--Ensemble Learning, Bagging & Random Forests
- 10.HPO Grid OPT & Bayesian OPT--HPO using Grid Search, Random Search & Bayesian Opt.
- 11.AdaBoost--AdaBoost (Adaptive Boosting)
- 12.GBDT--loss functions used in GBDT & optimizing GBDT using TPE
- 13.XGBoost--using XGBoost for regression and classification, exploring the concepts of three estimators and DART, Structure Score & Gain of Structure Score, and XGBoost hyper-opt using TPE
- 14.LightGBM--LightGBM, including Exclusive Feature Bundling(EFB), Gradient-based One-Side Sampling(GOSS), common hyperparameters, and the process of hyper-opt for LightGBM
- 15.CatBoost--CatBoost, a gradient boosting library designed for categorical feature support
- Practice--Practice
Deep Learning
- 01. NN based onTorch --create a basic neural network using PyTorch：
- 02. CNN --go through the process of building a Convolutional Neural Network
- 03. Training-image-classification-model --image classification model based on classic architecture
- 04. OpenCV
- 05. transformer & resnet
- 06. Classic Project for Object Detection
- 07. NLP Basic
- 08. Sentiment Analysis with LSTM
- 09. BERT 10. HuggingFace
Selfie_FLUX.1-dev_LoRA
- Selfie_FLUX.1-dev_LoRA--fine-tune a FLUX.1-dev with LoRA, Text-To-Image.
- Generated photos here
TimeSeries
- ARIMA--autoregressive integrated moving average model
