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11	Optimizing Inventory Management in B2C E-commerce using H2O AutoML : master's thesis / Оптимизация управления запасами в B2C электронной коммерции с использованием H2O AutoML Мридул, Ф. Т., Mridul, F. T. January 2024 (has links) In a rapidly changing and competitive business landscape for consumers (B2C) in e-commerce, effective inventory management is key to maintaining operational efficiency and ensuring customer satisfaction. The dissertation explores the application of automated machine learning models (AutoML) to improve inventory management processes. The result of the work is a comprehensive AutoML-based system has been developed for accurate demand forecasting, maintaining optimal inventory levels and simplified inventory replenishment based on the use of the H2O framework. / В условиях быстро меняющегося и конкурентного ландшафта бизнеса для потребителей (B2C) в сфере электронной коммерции эффективное управление запасами является ключевым фактором для поддержания операционной эффективности и обеспечения удовлетворенности клиентов. В диссертации исследуется применение автоматизированных моделей машинного обучения (AutoML) для улучшения процессов управления запасами. Результат работы - разработана комплексная система на основе AutoML для точного прогнозирования спроса, поддержания оптимальных уровней запасов и упрощенного пополнения запасов на основе использования фреймворка H2O. MASTER'S THESIS AUTOML INVENTORY MANAGEMENT B2C E-COMMERCE H2O DEMAND FORECASTING MACHINE LEARNING CUSTOMER RELATIONSHIP MANAGEMENT (CRM) STOCK OPTIMIZATION PREDICTIVE ANALYTICS УПРАВЛЕНИЕ ЗАПАСАМИ H2O МАШИННОЕ ОБУЧЕНИЕ ОПТИМИЗАЦИЯ ЗАПАСОВ
12	Analysis Of Fastlane For Digitalization Through Low-Code ML Platforms Raghavendran, Krishnaraj January 2022 (has links) Even a professional photographer sometimes uses automatic default settings that come up with the camera to take a photo. One can debate the quality of outcome from manual vs automatic mode. Until and unless we have a professional level of competence in taking a photo, updating our skills/knowledge as per the latest market trends and having enough time to try out different settings manually, it is worthwhile to use Auto-mode. As camera manufacturers, after several iterations of testing, comes up with the list of ideal parameter values, which is embedded as a factory default setting when we choose auto-mode. For non-professional photographers or amateurs recommend using the auto-mode that comes with the camera for not missing the moment. Similarly, in the context of developing machine learning models, until and unless we have the required data-engineering and ML development competence, time to train and test different ML models and tune different hyper parameter settings, it is worth to try out to Automatic Machine learning feature provided out-of-shelf by all the Cloud-based and Cloud-agnostic ML platforms. This thesis deep dives into evaluating possibility of generating automatic machine learning models with no-code/low-code experience provided by GCP, AWS, Azure and Databricks. We have made a comparison between different ML platforms on generating automatic ML model and presenting the results. It also covers the lessons learnt by developing automatic ML models from a sample dataset across all four ML platforms. Later, we have outlined machine learning subject matter expert’s viewpoints about using Automatic Machine learning models. From this research, we found automatic machine learning can come handy for many off-the-shelf analytical use-cases, this can be highly beneficial especially for time-constrained projects, when resource competence or staffing is a bottleneck and even when competent data scientists want a second-opinion or compare AutoML results with the custom ML model built. low-code no-code automL sagemaker machine learning vertex AI cloud agnostic digitailization cloud native Computer Systems Datorsystem Telecommunications Telekommunikation Communication Systems Kommunikationssystem Övrig annan teknik Information Systems, Social aspects Information Studies Biblioteks- och informationsvetenskap Human Aspects of ICT Mänsklig interaktion med IKT Information Systems Other Computer and Information Science Annan data- och informationsvetenskap Software Engineering Programvaruteknik

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Optimizing Inventory Management in B2C E-commerce using H2O AutoML : master's thesis / Оптимизация управления запасами в B2C электронной коммерции с использованием H2O AutoML

Analysis Of Fastlane For Digitalization Through Low-Code ML Platforms