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2190513_DS-ICE_2025s1

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2190513_DS-ICE_2025s1 최신버젼 다운로드

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# 2190513 Data Science (ICE) @CU (2025/1)

![Meme](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/meme.webp "Join DS")

## Syllabus:

[Syllabus](https://mycourseville-default.s3.ap-southeast-1.amazonaws.com/useruploaded_course_files/2025_1/70559/materials/Syllabus_2190513_DS_ICE_2025s1_v2-7075-17600037520770.pdf)

## Code:

### Week01: Intro to Numpy, Pandas

1. Pandas: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week01_Intro_Pandas/1_Pandas.ipynb)

2. Pandas with Youtube stat data: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week01_Intro_Pandas/2_Pandas_%28Dataset_Trending_YouTube_Video_Statistics%29.ipynb)

3. (Advanced) Pandas with Youtube stat data: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week01_Intro_Pandas/3_Advanced_Pandas_%28Dataset_Trending_YouTube_Video_Statistics%29.ipynb)

### Week02-03: Data Preparation

1. Impute Missing Value: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week02_DataPrep/Lab2_ImputeMissingValue_Pipeline.ipynb)

2. OneHotEncoder: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week02_DataPrep/Lab1_LoansDataSet.ipynb)

3. Outliers - Take Log: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week02_DataPrep/Lab4_Outliers_Titanic_Pipeline.ipynb)

4. Outliers - Remove them with Z-Score: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week02_DataPrep/Lab5_Outliers_Diabetes_(optional).ipynb>)

5. Split Train/Test: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week02_DataPrep/Lab3_SplitTrainTest.ipynb)

### Week04-07: Traditional ML

#### Week04: Tree-based model, Pipeline, Evaluation

#### Week05: Regression

#### Week06: kNN, GridSearch + Clustering

#### Week07: NN

1. Decision Trees: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/1_Decision_Trees_Random_Forests_v3.ipynb)

2. Linear Regression: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/2_Linear_Regression_v2.ipynb)

3. Logistic Regression: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/3_Logistic_Regression_v2.ipynb)

4. Neural Network: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/4_Neural_Network_v3.ipynb)

5. K Nearest Neighbors (GridSearchCV): [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/5_K_Nearest_Neighbors_v2_update_09012025.ipynb)

6. SVM: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/6_Support_Vector_Machine_v2.ipynb)

7. Save and Load Model: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/7_Save_Load_Model_v2.ipynb)

8. K-Means: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/8_K_Means_Clustering_v2.ipynb)

9. Market-Basket Analysis: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/9_Market_Basket_Intro_v2.ipynb)

10. Scikit-learn pipeline: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week03_ML/10_Scikit_learn_Pipeline.ipynb)

### Week08: Intro to Deep Learning

1. Image classification with CNN (PyTorch Lightning): [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/1_Image_classification_CIFAR10_CNN(lightning).ipynb>)

2-1. Image classification with EfficientNetV2s (PyTorch Lightning): [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/2_Image_classification_Animal_EfficientNetV2(lightning).ipynb>)

2-2. Image classification with EfficientNetV2s (PyTorch Lightning) with TensorBoard: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/2_2_Image_classification_Animal_EfficientNetV2(lightning)_TensorBoard.ipynb>)

2-3. Image classification with EfficientNetV2s (PyTorch Lightning) with Weights & Biases: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/2_3_Image_classification_Animal_EfficientNetV2(lightning)_wandb.ipynb>)

2-4. Image classification with EfficientNetb0 (Load a Pretrained Model from Hugging Face) (PyTorch Lightning) with Weights & Biases: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/2_4_Image_classification_Animal_EfficientNet(lightning)_wandb_HuggingFace.ipynb>)

3-1. Object detection with YOLOv8 (basic script): [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/3_2_Object_detection_VOCDetection_yolov8_basic.ipynb)

3-2. Object detection with YOLOv8 (custom dataset): [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/3_3_Object_detection_VOCDetection_yolov8_advanced.ipynb)

4. Semantic segmentation with deeplabv3 (PyTorch Lightning): [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/<https:/colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/4_Semantic_segmentation_Camseq_deeplabv3_DataInGD(lightning).ipynb>)

5. Time series Forecasting: Stock Price: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week08_DL/5_Time_series_forecasting_DataInGD_update.ipynb)

### Week09: Webscraping

1. Basic Web Scraping: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/webscraping/1_basic_web_scraping.ipynb)

2. Wiki Scraping Example: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/webscraping/2_wiki_scraping_example.ipynb)

3. REST API Extraction: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/webscraping/3_REST_API_extraction.ipynb)

4. Selenium: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/webscraping/4_selenium.ipynb)

### Week10: Fast API

1-1. Simple: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/1_simple.ipynb)

1-2. Simple Request: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/1_simple_request.ipynb)

2-1. Path Param: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/2_path_param.ipynb)

2-2. Path Param Request: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/2_path_param_request.ipynb)

3-1. Post: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/3_post.ipynb)

3-2. Post Request: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/3_post_request.ipynb)

4-1. Put: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/4_put.ipynb)

4-2. Put Request: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week09/fastapi/4_put_request.ipynb)

### Week11: Visualization with Streamlit

#### Streamlit Runner (for running files below in Colab) [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/streamlit_runner.ipynb)

1. Streamlit Layout: [🔗](https://github.com/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/1_streamlit_layout.py)

2. Streamlit Iris: [🔗](https://github.com/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/2_streamlit_iris.py)

3. Streamlit Gapminder: [🔗](https://github.com/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/3_streamlit_gapminder.py)

4. Streamlit Uber: [🔗](https://github.com/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/4_streamlit_uber.py)
5. Dash Histogram: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/5_dash_histograms.ipynb)

6. Dash Gapminder: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week10_Streamlit/6_dash_gapminder.ipynb)

### Week12: Advanced DL & Text Classification

1. Text Classification (TF-IDF) [`PyTorch`]: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week11_Text_Classification/5_2_tfidf_for_Sentiment_Analysis.ipynb)

2. Text Classification (BERT) [`PyTorch`]: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week11_Text_Classification/5_3_NLP_Transfer_Learning_for_Text_Classification_Using_Hugging_Face_Transformers_Trainer.ipynb#scrollTo=tQqHYsWVTV6D)

3. Text Classification (Phayathaibert) [`PyTorch Lightning`]: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week11_Text_Classification/5_4_Wongnai_Review_Rating_Classifiacation_(Pytorch_lightning).ipynb)

4. Multi-label Text Classification (microsoft/deberta-v3-small) [`PyTorch`]: [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week11_Text_Classification/5_5_Multi_label_Text_Classification.ipynb)

### Week13: Generative AI (Prompt Engineering, Monitoring, Agentic Workflow, RAG, Fine-tuning)

1. Basic API Call with LangChain [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_1_LLM_Basic_API_Call_LangChain.ipynb)

2. Basic Prompt Engineering [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_2_LLM_Prompt_Engineering_Basic_LangChain.ipynb)

3. Advanced Prompt Engineering [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_3_LLM_Prompt_Engineering_Advanced_LangChain.ipynb)

4. LangChain Playground and Tracking with LangSmith [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_4_LLM_LangChiain_Playground_Tracking_with_LangSmith.ipynb)

5. Basic LangGraph [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_5_LLM_Basic_LangGraph.ipynb)

6. RAG with LangChain and Agentic RAG with LangGraph [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_6_LLM_RAG_LangChain_LangGraph.ipynb)

<!--
7. Creating a Simple ReAct Agent using LangGraph [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_7_LLM_Create_a_ReAct_Agent.ipynb)

8. Fine-tuning a Local LLM (Typhoon-7B) [`Hugging Face`] [![Open In Colab](https://raw.githubusercontent.com/pvateekul/2190513_DS-ICE_2025s1/main/image/colab-badge.svg)](https://colab.research.google.com/github/pvateekul/2190513_DS-ICE_2025s1/blob/main/code/Week12_GenerativeAI/7_8_LLM_Typhoon7b_Finetuning_Huggingface.ipynb)
-->

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