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A configuration manual outlines system requirements, including OS, CPU, RAM, storage, optional GPU, and the Python/Anaconda, Jupyter Notebook, and IDE setup. It also describes project development phases such as importing libraries, dataset acquisition using a public supply-chain dataset, dataset import, and initial data cleaning and preprocessing concepts.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/forecasting-sales-and-inventory-in-supply-chain-using-machine-learning-methods-research-project-submission-sheet/290689/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/forecasting-sales-and-inventory-in-supply-chain-using-machine-learning-methods-research-project-submission-sheet/290689.png","ImageObject",300,407,{"name":42,"@type":43},"Levi","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-30","2026-09-17",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",17,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the project title and academic programme for this submission?","Question",{"text":63,"@type":64},"The project title is “Forecasting Sales and Inventory in Supply Chain using Machine Learning Methods” for an MSc in Data Analytics programme.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What minimum system requirements are recommended for the project?",{"text":68,"@type":64},"Recommended requirements include Windows 10/macOS/Linux (Ubuntu), an Intel Core i5 or AMD Ryzen 5 class CPU, at least 8GB RAM, SSD storage of 256GB, and an optional NVIDIA GTX/RTX GPU. Python 3.7+ with Anaconda, Jupyter Notebook, and an IDE such as Visual Studio Code or PyCharm are also recommended.",{"name":70,"@type":61,"acceptedAnswer":71},"What dataset and preparation steps are described in the configuration manual?",{"text":72,"@type":64},"The submission specifies using the DataCo Smart Supply Chain dataset downloadable from Mendeley, then covers importing the dataset and applying data cleaning and preprocessing to handle issues like missing data, outliers, and duplicate entries.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},290689,1789642366,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":80,"read_time":145,"preview_page_count":4},7971461740909,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Configuration Manual  \nMSc Research Project MSc in Data Analytics  \nRian Dwi Putra Student ID: 22108637  \nSchool of Computing National College of Ireland  \nSupervisor: Rejwanul Haque & John Kelly  \nNational College of Ireland MSc Project Submission Sheet School of Computing  \nStudent Name: Rian Dwi Putra  \nStudent ID: 22108637  \nProgramme: MSc in Data Analytics Year: 2023  \nModule: Research Project  \nLecturer: Rejwanul Haque & John Kelly  \nSubmission Due  \nDate: August 14 2023  \nProject Title: Forecasting Sales and Inventory in Supply Chain using Machine Learning Methods  \nWord Count: 1149 Page Count: 9  \nI hereby certify that the information contained in this (my submission) is information pertaining to research I conducted for this project. All information other than my own contribution will be fully referenced and listed in the relevant bibliography section at the rear of the project.  \nALL internet material must be referenced in the bibliography section. Students are required to use the Referencing Standard specified in the report template. To use other author's written or electronic work is illegal (plagiarism) and may result in disciplinary action.  \nSignature: Rian Dwi Putra  \nDate: August 14 2023  \nPLEASE READ THE FOLLOWING INSTRUCTIONS AND CHECKLIST  \n\n| Attach a completed copy of this sheet to each project (including multiple copies) | □ |\n| --- | --- |\n| Attach a Moodle submission receipt of the online project submission, to each project (including multiple copies) . | □ |\n| You must ensure that you retain a HARD COPY of the project, both for your own reference and in case a project is lost or mislaid. It is not sufficient to keep a copy on computer. | □ |\n\nAssignments that are submitted to the Programme Coordinator Office must be placed into the assignment box located outside the office.  \n\n| Office Use Only |  |\n| --- | --- |\n| Signature: |  |\n| Date: |  |\n| Penalty Applied (if applicable): |  |\n\nConfiguration Manual  \nRian Dwi Putra  \n22108637  \n1 Introduction  \nYou will gain a better understanding of the project's system requirements from this configuration manual. The research project's hardware/software platforms, data sources, code, figures, and files are all described in this configuration manual. Implementing the research project “Forecasting Sales and Inventory in Supply Chain using Machine Learning Methods” will be made easier with this manual.  \n2 System Requirements  \nThe following minimum system requirements are suggested for this data analytics projects:  \n1. Working Framework: Windows 10, macOS, or Linux (Ubuntu) .  \n2. Processor: Intel Core i5 or AMD Ryzen 5 (or equivalent) for basic machine learning tasks.  \n3. RAM: 8 GB or greater RAM is beneficial for handling bigger datasets and complex models.  \n4. Storage: SSD (Solid State Drive) with 256 GB for quicker access to data and model training.  \n5. Graphics Processing Unit (GPU): A GPU (NVIDIA GTX or RTX series) can significantly accelerate model training for advanced projects, even though it is not necessary for basic projects.  \n6. Python and Anaconda: Install Python 3.7 or later which comes with essential libraries like NumPy, Pandas, and scikit-learn, needs to be installed alongside Python 3.7 or later.  \n7. Jupyter Notebook: For intelligent coding and visualization.  \n8. Integrated Development Environment (IDE): Visual Studio Code, PyCharm, or Jupyter Lab are IDEs that are recommended.  \n9. Internet connection: To get to online resources, datasets, and machine learning libraries.  \n3 Project Development  \n3.1 Importing Libraries  \nImporting libraries in Python means adding external code modules or packages to the current Python program to make it more useful. Python offers a vast ecosystem of libraries and bundles that give pre-composed code to different tasks, for example, data manipulation, visualization, machine learning, and more. At the point when importing a library, we will get access to its capabilities, classes, and variables, enable i","cbCainGYf0sCfi3u","https://ap.wps.com/l/cbCainGYf0sCfi3u","pdf",812921,11,"English","# 1 Introduction\n# 2 System Requirements\n# 3 Project Development\n## 3.1 Importing Libraries\n## 3.2 Dataset\n### 3.2.1 Importing Dataset\n### 3.2.2 Data Cleaning & Preprocessing","[{\"question\":\"What is the project title and academic programme for this submission?\",\"answer\":\"The project title is “Forecasting Sales and Inventory in Supply Chain using Machine Learning Methods” for an MSc in Data Analytics programme.\"},{\"question\":\"What minimum system requirements are recommended for the project?\",\"answer\":\"Recommended requirements include Windows 10/macOS/Linux (Ubuntu), an Intel Core i5 or AMD Ryzen 5 class CPU, at least 8GB RAM, SSD storage of 256GB, and an optional NVIDIA GTX/RTX GPU. Python 3.7+ with Anaconda, Jupyter Notebook, and an IDE such as Visual Studio Code or PyCharm are also recommended.\"},{\"question\":\"What dataset and preparation steps are described in the configuration manual?\",\"answer\":\"The submission specifies using the DataCo Smart Supply Chain dataset downloadable from Mendeley, then covers importing the dataset and applying data cleaning and preprocessing to handle issues like missing data, outliers, and duplicate entries.\"}]","Forecasting Sales and Inventory in Supply Chain using Machine Learning Methods - Research Project Submission Sheet | PDF",28]