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MOOC
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand.
Accordingly, in this course, you will learn:
- The major steps involved in tackling a data science problem.
- The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
- How data scientists think!
- Course related:
- LGT6202: Stochastic Models and Decision under Uncertainty, LGT6802 Guided Study in Logistics II, LGT6803: Guided Study in Logistics III, and LGT6801 Guided Study in Logistics I
- Subjects:
- Business Information Technology and Computing, Data Science and Artificial Intelligence
- Keywords:
- Data mining Problem solving Electronic data processing
- Resource Type:
- MOOC
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Others
Fuzzy Logic Toolbox™ provides MATLAB® functions, apps, and a Simulink® block for analyzing, designing, and simulating systems based on fuzzy logic. The product guides you through the steps of designing fuzzy inference systems. Functions are provided for many common methods, including fuzzy clustering and adaptive neurofuzzy learning. The toolbox lets you model complex system behaviors using simple logic rules, and then implement these rules in a fuzzy inference system. You can use it as a stand-alone fuzzy inference engine. Alternatively, you can use fuzzy inference blocks in Simulink and simulate the fuzzy systems within a comprehensive model of the entire dynamic system.
- Course related:
- SD5804 Design Research Methods
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mathematics and Statistics
- Keywords:
- Fuzzy systems Fuzzy logic
- Resource Type:
- Others
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Others
Agent based modeling focuses on the individual active components of a system. This is in contrast to both the more abstract system dynamics approach, and the process-focused discrete event method. With agent based modeling, active entities, known as agents, must be identified and their behavior defined. They may be people, households, vehicles, equipment, products, or companies, whatever is relevant to the system. Connections between them are established, environmental variables set, and simulations run. The global dynamics of the system then emerge from the interactions of the many individual behaviors. AnyLogic combines professional discrete event, system dynamics, and agent based modeling in one platform for efficient, no compromise results. In our white paper, Multimethod Simulation Modeling for Business Applications, we investigate these three main simulation modeling approaches and construct a multimethod model example to illustrate the advantages of multimethod simulation modeling. Read the white paper and see why hybrid models are always a better choice!
- Course related:
- CE631 Simulation and IT Applications in Construction
- Subjects:
- Computing, Data Science and Artificial Intelligence and Business Information Technology
- Keywords:
- Multiagent systems Computer simulation System analysis -- Data processing
- Resource Type:
- Others
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Video
This channel contains a complete list of physics videos, as well as hundreds of chemistry, astronomy, math, and mechanical engineering videos. The physics videos explain the fundamental concepts of physics with some easy to follow examples on how to solve physics problems. The chemistry videos cover all the basic topics of chemistry, the astronomy videos explain the wonders of Earth and our Universe, and the math videos cover many topics in algebra, trigonometry, pre-calculus, calculus and differential equations.
- Subjects:
- Mechanical Engineering, Physics, Mathematics and Statistics, Electrical Engineering, Chemistry, and Cosmology and Astronomy
- Keywords:
- Physics Mechanical engineering Astronomy Kalman filtering Mathematics Electrical engineering Chemistry
- Resource Type:
- Video
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Others
Learning cyber security on TryHackMe is fun and addictive. Earn points by answering questions, taking on challenges and maintain your hacking streak through short lessons. Learn by following a structured paths and reinforce your skills in a real-world environment by completing guided, objective-based tasks and challenges.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer security
- Resource Type:
- Others
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Video
課程簡介：微分表切線斜率，積分表曲線下圍出的面積，兩截然不同的東西透過微積分基本定理連結在一起。
- Course related:
- AMA1007 Calculus and Linear Algebra
- Subjects:
- Mathematics and Statistics
- Keywords:
- Calculus
- Resource Type:
- Video
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Video
Welcome to Zero to Hero for Natural Language Processing using TensorFlow! If you’re not an expert on AI or ML, don’t worry -- we’re taking the concepts of NLP and teaching them from first principles with our host Laurence Moroney.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Natural language processing (Computer science) Machine learning
- Resource Type:
- Video
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Others
Colaboratory, or "Colab" for short, allows you to write and execute Python in your browser, with
(1) Zero configuration required
(2) Free access to GPUs
(3) Easy sharing
Whether you're a student, a data scientist or an AI researcher, Colab can make your work easier. Watch Introduction to Colab to learn (https://www.youtube.com/watch?v=inN8seMm7UI) more, or just get started below!
- Course related:
- COMP3011 Machine Learning and Data Analytics
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language) Computer programming Computer science
- Resource Type:
- Others
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Courseware
In this card, we are going to help you understand the general concept of Binary Search.
Binary Search is one of the most fundamental and useful algorithms in Computer Science. It describes the process of searching for a specific value in an ordered collection.
Terminology used in Binary Search:
(1) Target - the value that you are searching for
(2) Index - the current location that you are searching
(3) Left, Right - the indicies from which we use to maintain our search Space
(4) Mid - the index that we use to apply a condition to determine if we should search left or right
- Course related:
- COMP3011 Design and Analysis of Algorithms
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer algorithms
- Resource Type:
- Courseware
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e-journal
In this journal platform, you can find the articles which published under the Creative Commons Attribution-NonCommercial 4.0 International License. The journal covers a various disciplines, including:
Biomedical & Life Sciences
Business & Management
Chemistry & Material Science
Computer & Communications
Earth & Environmental Science
Engineering
Humanities
Physics & Mathematics
Social Sciences
- Subjects:
- Computing, Data Science and Artificial Intelligence, Chemistry, Management, Environmental Sciences, Biology, Physics, and Mathematics and Statistics
- Keywords:
- Chemistry Management Environmental sciences Physics Industrial management Mathematics Social Sciences Engineering Humanities Computer science Biology
- Resource Type:
- e-journal