Intern(Chow Jun Hoe)

 10/9/2025 Today, I reviewed the data filtering methods I used in Python during my internship. By reviewing common Pandas syntax, such as loc and isin, and combining conditional filtering, I gained a clearer understanding of how to quickly extract the required data based on different conditions.

 9/9/2025 Today, I started applying the Excel functions I learned yesterday to real-world data processing, operating and validating real sales and inventory data. For example, I used VLOOKUP and INDEX MATCH to match information from different tables.

 8/9/2025 Today, I continued to revise and optimize the summary, focusing on improving the explanation of the data analysis methods to make the overall content clearer. After completing the revisions, I began to learn how to use Excel functions, including common formulas such as VLOOKUP, INDEX, MATCH, and IF. I also tried to apply these functions to daily data analysis to improve the efficiency of data processing and filtering.

 5/9/2025 Public Holiday

 4/9/2025 Today, I presented the content I prepared the day before to the team. I detailed the process of building the predictive model, its performance in different scenarios, and its limitations. During the presentation, the manager offered suggestions for improvements to some of the data processing methods and feature design.

 3/9/2025 Today, I continued my in-depth study of the principles and structure of the N-BEATS model, including its time series forecasting mechanism based on a feedforward neural network, its trend and seasonality decomposition methods, and its strengths and limitations in long-term forecasting. Integrating this with EcoShop's sales data, I began to consider how, building on existing feature engineering, N-BEATS could be applied to forecasting scenarios involving special factors such as holidays and price fluctuations.

 2/9/2025 My main task today was to complete and refine the presentation for tomorrow's presentation, ensuring that all slides were logically clear, data accurate, and case studies complete. I reviewed and fine-tuned each model's prediction results and their strengths and weaknesses, optimizing the presentation order and chart layout to more intuitively showcase the analysis results and learnings from my internship.