[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119050-en":3,"doc-seo-119050-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119050,137441390410,"Hazel","https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984",8,"Research & Report","Data Pipeline Training - Integrating AutoML to Optimize the Data Flow of Machine Learning Models - Overview and Key Concepts","Data Pipeline training underpins machine learning modeling and the delivery of data products, especially as data sources diversify and data volumes expand rapidly. The paper integrates AutoML with data pipeline design to automate and optimize data flow, using automation to improve the intelligence of pipeline operations. It outlines how optimized, adaptive pipelines support more effective machine learning outcomes, accelerate the modeling workflow, and address complex problems across evolving data environments.","Data Pipeline Training: Integrating AutoML to Optimize the Data Flow of Machine Learning Models  \nJiang Wu1,*  \nComputer Science University of Southern California, Los Angeles, CA, USA [jiangwu@usc.edu](jiangwu@usc.edu)  \nChunhe Ni2  \nComputer Science University of Texas at Dallas, Richardson, TX, USA [nichunhe@outlook.com](nichunhe@outlook.com)  \nHongbo Wang 1  \nComputer Science University of Southern California Los Angeles, CA [hongbowa@usc.edu](hongbowa@usc.edu)  \nChenwei Zhang3  \nElectrical and Computer Engineering University of Illinois Urbana-Champaign Urbana, IL [zchenwei66@gmail.com](zchenwei66@gmail.com)  \nWenran Lu4  \nElectrical Engineering University of Texas at Austin Austin, TX [wenranlu@gmail.com](wenranlu@gmail.com)  \nAbstract—Data Pipeline plays an indispensable role in tasks such as modeling machine learning and developing data products. With the increasing diversification and complexity of Data sources, as well as the rapid growth of data volumes, building an efficient Data Pipeline has become crucial for improving work efficiency and solving complex problems. This paper focuses on exploring how to optimize data flow through automated machine learning methods by integrating AutoML with Data Pipeline. We will discuss how to leverage AutoML technology to enhance the intelligence of Data Pipeline, thereby achieving better results in machine learning tasks. By delving into the automation and optimization of Data flows, we uncover key strategies for constructing efficient data pipelines that can adapt to the everchanging data landscape. This not only accelerates the modeling process but also provides innovative solutions to complex problems, enabling more significant outcomes in increasingly intricate data domains.  \nKeywords-Data Pipeline Training;AutoML; Data environment; Machine learning  \nI. INTRODUCTION  \nThe use of Machine Learning techniques and methods to solve practical problems has been successfully applied to many fields, and we often see examples of personalized recommendation systems, financial anti-fraud, natural language processing and machine translation, pattern recognition, intelligent control and so on. typical machine learning process usually includes source data ETL, data preprocessing, index extraction, model training, cross-validation, and new data prediction, among others. In today's real-world data work, the data we need to deal with is often diverse[1]. For example, imagine this scenario: if we need to do some analysis of a product, the source of data may be from social media user  \nreviews, click rates, or transaction data obtained from sales channels, or historical data, or product information captured from product websites. In the face of so many different data sources, the data you have to deal with may include CSV files, may also have JSON files, Excel and other forms, may be pictures and text, may also be stored in the database table, and may be from the website, APP real-time data. This paper focuses on data pipeline training: Integrated AutoML takes optimizing the data flow of machine learning model as its core content, and analyzes the integrated optimization model and experimental process of data pipeline.  \nII. OVERVIEW OF RELATED CONCEPTS  \nA. Data pipeline definition and function  \nA data pipeline is a system used to automate the processing and transmission of data. It can extract the data from the source system, through cleaning, conversion, loading and other steps, and then transfer to the target system. The main function of data pipeline is to improve the efficiency of data processing, ensure the accuracy of data, and ensure the security of data. In traditional data processing, manual operations take up most of the time. The data pipeline through the automatic way, can greatly improve the efficiency of data processing. For example, a data pipeline can automate data processing at regular intervals by setting up scheduled tasks. In this way, it can not only reduce the time a","cbCaidbkllf7bczW","https://ap.wps.com/l/cbCaidbkllf7bczW","pdf",582434,1,5,"English","en",105,"# Introduction\n# Overview of Related Concepts\n## Data pipeline definition and function\n## Data Pipeline and machine learning\n## Pipeline analysis of the execution process","[{\"question\":\"Why is data pipeline training important for machine learning?\",\"answer\":\"A data pipeline automates extraction, cleaning, conversion, and loading, improving processing efficiency while supporting accuracy and security. Training focuses on optimizing the data flow so machine learning modeling becomes more effective and scalable.\"},{\"question\":\"How does integrating AutoML help optimize the data flow?\",\"answer\":\"AutoML automates decisions and optimization within the pipeline, enhancing how the pipeline handles diverse data sources. This improves intelligence in data handling and leads to better machine learning results.\"},{\"question\":\"What core functions does a data pipeline provide?\",\"answer\":\"A data pipeline improves processing efficiency, ensures data accuracy through cleaning and verification rules, and supports data security by reducing errors and human-related issues during manual operations.\"}]","Data Pipeline Training - Integrating AutoML to Optimize the Data Flow of Machine Learning Models - Overview and Key Concepts | PDF",1785722088,13,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"data-pipeline-training-integrating-automl-to-optimize-the-data-flow-of-machine-learning-models-overview-and-key-concepts","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/data-pipeline-training-integrating-automl-to-optimize-the-data-flow-of-machine-learning-models-overview-and-key-concepts/119050/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is data pipeline training important for machine learning?","Question",{"text":75,"@type":76},"A data pipeline automates extraction, cleaning, conversion, and loading, improving processing efficiency while supporting accuracy and security. Training focuses on optimizing the data flow so machine learning modeling becomes more effective and scalable.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does integrating AutoML help optimize the data flow?",{"text":80,"@type":76},"AutoML automates decisions and optimization within the pipeline, enhancing how the pipeline handles diverse data sources. This improves intelligence in data handling and leads to better machine learning results.",{"name":82,"@type":73,"acceptedAnswer":83},"What core functions does a data pipeline provide?",{"text":84,"@type":76},"A data pipeline improves processing efficiency, ensures data accuracy through cleaning and verification rules, and supports data security by reducing errors and human-related issues during manual operations.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,109,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":21,"slug":137},19,"General","general"]