鉁夛笍 聽Get in touch on LinkedIn & Stack Overflow 馃寧
馃搨 My Projects:
Machine Learning (ML):
- 馃 Brain MGMT Prediction: Comprehensive analysis and model development for MGMT prediction using an XGBoost ensemble with a U-Net-based feature extractor. | Kaggle |
Deep Neural Networks (DNN):
- 馃嵎 Wine Quality Prediction: Utilized DNN to predict wine quality based on physicochemical properties. | Kaggle |
Computer Vision (CV):
- 馃 Brain MGMT Prediction: Developed a CNN-based model for prediction of the MGMT. | Kaggle |
- 馃尵 Rice Grain Classification: Employed CNN to classify different types of rice grains. | Kaggle |
- 馃殾 Traffic Sign Recognition (GTSRB): Developed a CNN-based model for real-time traffic sign recognition. | Kaggle |
- 鉁嶏笍 Handwritten Digit Classification (MNIST): Achieved high accuracy in classifying handwritten digits using CNN. | Kaggle |
Generative Adversarial Network (GAN)
- 馃毑 Bicycle Image Generation: Exploration of Generative Models (GAN) and its capabilities, focusing on the generation of bicycle. | Kaggle |
- Base Stemming and Lemmatization
- Base Stemming Lemmatization Classification
- Base TF-IDF Similarity
- Base Neural Word Embeddings
- Weaviate VectorDB
- Weaviate Nearest Neighbors
- Weaviate CRUD Search
- Weaviate Sparse Dense Hybrid Search
- Weaviate Multilingual Search
- Weaviate Search
- Weaviate Dense Retrieval
- Weaviate ReRank
- RAG LLamaIndex Pipeline
- RAG LLamaIndex Sentence Window Retrieval
- RAG LLamaIndex Auto Merging Retrieval
- RAG LLamaIndex Ollama Auto Merging Retrieval
- RAG Agent