semvec/pypi-packages huggingface dataset:
say-week1-knn 0.1.0
Week1 program - using scikit-learn KNeighborsClassifier
License: MIT
Requires Python: >=3.8

# knn [K-Nearest Neighbor Classifier]
Weekly Programming no. #1: KNN
- Using `sklearn.neighbors.KNeighborsClassifier`

### 프로그램 동작 방식
- [ ] 학습된 모델이 없는 상태에서 출발
- [ ] 길이 `length`, 무게 `weight` 데이터를 입력 > 프로그램이 예측 값을 출력
- [ ] 예측값 출력 후 프롬프트를 통해 사용자가 예측값의 정답 유무를 다시 입력
- [ ] 위 과정을 반복하며 모델을 최적화

## Usage
keywordsai-eval 0.1.9
An evaluation package for LLM input output
License: MIT
Requires Python: <4.0,>=3.9

# Keywords AI Eval
Keywords AI eval is an open-sourced evaluation package for classification


## Get started
Installation
```
pip install keywordsai-eval
```

# Sample questions
What are the main features of Keywords AI, and how do they benefit developers?

Can you walk me through the process of setting up Keywords AI in a Python project using the OpenAI SDK?

How does Keywords AI's unified LLM API work, and what advantages does it offer over using individual APIs for different models?

What kind of monitoring and observability features does Keywords AI provide for LLM applications?

What kind of monitoring and observability features does Keywords AI provide for LLM applications?k