112-2 師大科技系程式語言 (Programming Language at National Taiwan Normal University (NTNU) in 2024)

授課教師：蔡芸琤老師(Pecu)

姓名：鍾孟傑(Michael)

系級：選讀生 (學號: 91299217Y)

HW1

• Read the data using Python Pandas and convert the DataFrame to a Set data type.
• Utilize the characteristics of the Set data type to perform union, intersection, and difference analyses.
• Explain the results of the analysis.

HW2

• Perform EDA on store sales data from Kaggle.
• Build machine learning model to predict store sales.
• Make hypothesis based on the previous result and then optimize the the model.
• Summarize the results of the analysis.

HW3

• Clean the scraped website content using regular expressions.
• Structure the relevant data into two formats: a DataFrame and a dictionary (you may modularize the code as desired).
• Export these two data formats into CSV and JSON files, respectively.
• Create an explanatory video of the code and upload it to YouTube.

HW4

• Continue exploring the dataset obtained from Assignment Three's web scraping.
• Extract features from the unstructured data.
• Use jieba for word segmentation and obtain keyword frequencies.
• Obtain a summary using an LLM (Large Language Model), then extract keywords from the summary.
• Visualize these features using an association graph.

最新筆記

• Sync files between local and GitHub: use GitHub Desktop
• Exercise: Demostrating LLM with RAG

• Exercise: Data visualization practice

• Exercise: Json data practice

• Exercise: Regex practice

• Exercise: Web scraping practice

• No class (Tomb Sweeping Day)

• Exercise: Data cleaning & Data Visualization

• Exercise: HuggingFace pipline practice

• Exercise: Try multiple LLM models on HuggingFace

• Exercise: Data & Text mining on moview review by LLM

• Exercise: Langchain practice

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