AI產品開發維運(MLOps)之迭代歷程分享 The Journey of AI Product Development and Improvement

張仲樸 Enzo Chang

張仲樸 Enzo Chang

I'm Enzo, an atypical developer with experience covering Data x Software x Education, working as a Data Engineer & Scrum Master in e-commerce company, focusing on ETL, Data Pipeline, MLOps, Crawler & RESTful API. Passionate about learning and sharing. I have been a volunteer and speaker in the Data & Agile community for a long time, and I have served as a Python Web Crawler course lecturer in the company. 👋 Feel free to contact me! Linkedin ➡️ https://www.linkedin.com/in/enzochang/

黃奕鳴 Polo Huang

黃奕鳴 Polo Huang

As a software engineer with 4 years of experience in the E-commerce industry, I've been in charge of ML Ops and Data Pipeline by Python. Furthermore, my focus area also includes FastAPI, MySQL, and Docker. As for career planning in the next few years, implementing machine learning models and learning ML Ops are my major objectives. 👋 Feel free to contact me! LinkedIn: www.linkedin.com/in/yiming-huang-6026601b3

    Abstract

    MLOps 是機器學習(Machine Learning) 與軟體開發維運(DevOps) 結合的縮寫,近年來業界將 AI產品化特別受重視的領域,因為 ML/DL 模型離開實驗環境,將面臨更多效能、穩定性、持續優化等挑戰。本演講以企業內部的產品為例子,分享我們在實務上如何讓商業需求以及技術研究落地,在完全基於 Python 的環境,從零打造出基礎可用的系統,到經過兩階段迭代升級的現行版本,過程中在架構設計與工具選擇上所遇到的瓶頸和困難點,以及我們的解決方式。

    Description

    Video

    Location

    R0

    Date

    Day 2 • 12:45-13:15 (GMT+8)

    Language

    Chinese talk w. English slides

    Level

    Intermediate

    Category

    Application