Advanced Big Data Analytics - Phân tích dữ liệu lớn nâng cao (Lecture 2)
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E6895 Advanced Big Data and AI Lecture 2: Big Data Foundations Ching-Yung Lin, Ph.D. Adjunct Professor, Dept. of Electrical Engineering and Computer Science January 27th, 2023 E6895 Advanced Big Data Analytics — Lecture 2 © CY Lin, 2023 Columbia University Milestone 1 Instruction 2 E6895 Advanced Big Data and AI – Lecture 2: Big Data Foundations © 2023 CY Lin, Columbia University Milestone 1 Each team will present on either February 3rd or February 10th Prepare about 10-12 mins of presentation (and expect 3-5 mins of Q&A) All teams will submit a written Milestone 1 report on February 10th. Key elements in Milestone 1 presentation: Task Goal: What do you want to achieve? Why is the research and development important? Is this a new topic that considers challenges of Volume Velocity Variety Does this topic try to incorporate multi-discipline knowledge? 3 EE6895 Advanced Big Data and AI — Lecture 2 © 2022 CY Lin, Columbia University Milestone 1 Literature Survey: What are the prior arts? What related works were done before? Which research publications, tools and products may be utilized to build upon them to achieve the goal? Methodology: What types of novel algorithms I shall try to invent and implement? Where will you try to gather the data — Existing dataset? Selfcollected dataset? Live dataset? 4 EE6895 Advanced Big Data and AI — Lecture 2 © 2022 CY Lin, Columbia University Milestone 1 System: What will your nal system look like — potential backend components and interaction with front end? How will you create visualization and user interface to help users consume your analysis outcome? Timeline: What may you achieve in Milestones 2 and 3, and in the Final Project? Note — it’s good to think about what you want to achieve as complete as possible and study what other people have done. But, like all projects, everything can change when you make progress. Please do not afraid of making bold assumptions
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- Advanced Big Data Analytics - Phân tích dữ liệu lớn nâng cao (Lecture 2)
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- Columbia University · Big Data
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