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In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.
- Course related:
- AMA1600 Fundamentals of AI and Data Analytics and AMA1751 Linear Algebra
- Subjects:
- Mathematics and Statistics and Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Others
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MOOC
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
- Course related:
- AAE5103 Artificial Intelligence in Aviation Industry
- Subjects:
- Computing
- Keywords:
- Machine learning Artificial intelligence
- Resource Type:
- MOOC
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Others
All resources and notes from the Complete Web Developer in 2022: Zero to Mastery course
- Course related:
- COMP3421 Web Application Design and Development, LGT3109 Introduction to Coding for Business with Python, COMP3211 Software Engineering, and COMP1001 Problem Solving Methodology in Information Technology
- Subjects:
- Computing
- Keywords:
- Web sites -- Design Web site development
- Resource Type:
- Others
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Others
Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access GPUs at no cost to you and a huge repository of community published data & code. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time.
- Subjects:
- Computing
- Keywords:
- Machine learning Artificial intelligence Big data
- Resource Type:
- Others
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Others
We offer mathematics in an enjoyable and easy-to-learn manner, because we believe that mathematics is fun.
- Subjects:
- Mathematics and Statistics
- Keywords:
- Mathematics
- Resource Type:
- Others
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Video
Lecture videos from Gilbert Strang's course on Linear Algebra at MIT.
- Course related:
- AMA1120 Basic Mathematics II - Calculus and Linear Algebra
- Subjects:
- Mathematics and Statistics
- Keywords:
- Algebras Linear
- Resource Type:
- Video
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Video
This course is an introduction to game theory and strategic thinking. Ideas such as dominance, backward induction, Nash equilibrium, evolutionary stability, commitment, credibility, asymmetric information, adverse selection, and signaling are discussed and applied to games played in class and to examples drawn from economics, politics, the movies, and elsewhere.
- Subjects:
- Mathematics and Statistics and Economics
- Keywords:
- Game theory
- Resource Type:
- Video
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Video
Before the advent of computers around 1950, optimization centered either on small-dimensional problems solved by looking at zeroes of first derivatives and signs of second derivatives, or on infinite-dimensional problems about curves and surfaces. In both cases, "variations" were employed to understand how a local solution might be characterized. Computers changed the picture by opening the possibility of solving large-scale problems involving inequalities, instead of only equations. Inequalities had to be recognized as important because the decisions to be optimized were constrained by the need to respect many upper or lower bounds on their feasibility. A new kind of mathematical analysis, beyond traditional calculus, had to be developed to address these needs. It built first on appealing to the convexity of sets and functions, but went on to amazingly broad and successful concepts of variational geometry, subgradients, subderivatives, and variational convergence beyond just that. This talk will explain these revolutionary developments and why there were essential.
Event date: 1/11/2022
Speaker: Prof. Terry Rockafellar (University of Washington)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex functions Convex sets Mathematical optimization Computer science -- Mathematics
- Resource Type:
- Video
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Video
Adaptive computation is of great importance in numerical simulations. The ideas for adaptive computations can be dated back to adaptive finite element methods in 1970s. In this talk, we shall first review some recent development for adaptive methods with some application. Then, we will propose a deep adaptive sampling method for solving PDEs where deep neural networks are utilized to approximate the solutions. In particular, we propose the failure informed PINNs (FI-PINNs), which can adaptively refine the training set with the goal of reducing the failure probability. Compared with the neural network approximation obtained with uniformly distributed collocation points, the proposed algorithms can significantly improve the accuracy, especially for low regularity and high-dimensional problems.
Event date: 18/10/2022
Speaker: Prof. Tao Tang (Beijing Normal University-Hong Kong Baptist University United International College)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Sampling (Statistics) Differential equations Partial -- Numerical solutions Mathematical models Adaptive computing systems
- Resource Type:
- Video
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MOOC
Operations management deals with operational planning and control issues, and is needed in all sectors of the society. One of the challenges to operations manager is how to make use of the available resources in the best way for meeting a certain objective. Quantitative approaches are inevitably needed in tackling many of such problems. Operations Research (OR) deals with problem formulation and application of analytical methods to assist in decision-making of operational problems in planning and control. The techniques of OR are useful quantitative tools to assist operations managers, and has a wide applicability in engineering, manufacturing, construction, financial and various service sectors. Operations Research is an applied mathematics subject and is also a course in many engineering and management programmes. This course is designed for both students learning OR and learners who are practitioners in their respective professionals. The mathematical procedures for the OR techniques are introduced in details in the examples provided in the course. This helps learners to master the methodology and the techniques and apply them to achieve their goals through active learning. This course introduces two prominent OR techniques and their extended topics. The Simplex Method for Linear Programming (LP) has been considered one of the top 10 algorithms of the 20th century. LP is an optimization technique for solving problems such as finding the optimal product mix, production plan, and shipment allocation, in order to maximize the profir or minimize the cost. The Critical Path Method (CPM) is a popular technique employed by project managers in scheduling project activities. Some extended topics of CPM are also introduced to deal with certain special situations in project management. In reality, many systems operate under stochastic environment and the operational problems cannot be solved by the known analytical methods. To this end, the simulation approach is introduced in the last chapter of this course. Simulation is a powerful technique for tackling OR problems under such situations.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Operations research
- Resource Type:
- MOOC
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Video
Convex Matrix Optimization (MOP) arises in a wide variety of applications. The last three decades have seen dramatic advances in the theory and practice of matrix optimization because of its extremely powerful modeling capability. In particular, semidefinite programming (SP) and its generalizations have been widely used to model problems in applications such as combinatorial and polynomial optimization, covariance matrix estimation, matrix completion and sensor network localization. The first part of the talk will describe the primal-dual interior-point methods (IPMs) implemented in SDPT3 for solving medium scale SP, followed by inexact IPMs (with linear systems solved by iterative solvers) for large scale SDP and discussions on their inherent limitations. The second part will present algorithmic advances for solving large scale SDP based on the proximal-point or augmented Lagrangian framework In particular, we describe the design and implementation of an augmented Lagrangian based method (called SDPNAL+) for solving SDP problems with large number of linear constraints. The last part of the talk will focus on recent advances on using a combination of local search methods and convex lifting to solve low-rank factorization models of SP problems.
Event date: 11/10/2022
Speaker: Prof. Kim-Chuan Toh (National University of Singapore)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Semidefinite programming
- Resource Type:
- Video
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Video
We introduce a Dimension-Reduced Second-Order Method (DRSOM) for convex and nonconvex (unconstrained) optimization. Under a trust-region-like framework, our method preserves the convergence of the second-order method while using only Hessian-vector products in two directions. Moreover; the computational overhead remains comparable to the first-order such as the gradient descent method. We show that the method has a local super-linear convergence and a global convergence rate of 0(∈-3/2) to satisfy the first-order and second-order conditions under a commonly used approximated Hessian assumption. We further show that this assumption can be removed if we perform one step of the Krylov subspace method at the end of the algorithm, which makes DRSOM the first first-order-type algorithm to achieve this complexity bound. The applicability and performance of DRSOM are exhibited by various computational experiments in logistic regression, L2-Lp minimization, sensor network localization, neural network training, and policy optimization in reinforcement learning. For neural networks, our preliminary implementation seems to gain computational advantages in terms of training accuracy and iteration complexity over state-of-the-art first-order methods including SGD and ADAM. For policy optimization, our experiments show that DRSOM compares favorably with popular policy gradient methods in terms of the effectiveness and robustness.
Event date: 19/09/2022
Speaker: Prof. Yinyu Ye (Stanford University)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Nonconvex programming Mathematical optimization
- Resource Type:
- Video
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Video
This mini lecture gives an overview on the principles underlying food spoilage and introduces different unit operations of food processing.
- Subjects:
- Food Science
- Keywords:
- Food industry trade Processed foods Food science
- Resource Type:
- Video
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Video
An online lecture on the topic of "Ultrasound: Application in Food Science and Technology". The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Food Science
- Keywords:
- Ultrasonic imaging Food science
- Resource Type:
- Video
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Video
An online lecture on the topic of "Chemical Reaction in Atmosphere".The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Environmental Sciences
- Keywords:
- Environmental chemistry Atmospheric chemistry
- Resource Type:
- Video
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Video
This mini-lecture discusses the science of global warming, impact of greenhouse gases (GHGs) emission to life on earth, and the mitigation strategies for climate change. The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Chemistry and Environmental Sciences
- Keywords:
- Greenhouse gases Global warming
- Resource Type:
- Video
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Video
This mini-lecture introduces the future battery. The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Physics and Chemistry
- Keywords:
- Storage batteries
- Resource Type:
- Video
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Video
This mini-lecture on the topic of "Tailoring The Smallest Machinery into Future Robotic Systems". The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Nanotechnology
- Keywords:
- Robotics Robots -- Design construction Nanotechnology
- Resource Type:
- Video
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Video
This mini-lecture introduces different types of microorganisms that are commonly found in food. The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Food Science
- Keywords:
- Bacteria Foodborne diseases -- Microbiology
- Resource Type:
- Video
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Video
This mini-lecture focuses on basic analytical chemistry and the science behind Crime Scene Investigation (CSI). The Faculty of Applied Science and Textiles (FAST) and the Institute of Textiles & Clothing (ITC) organized the mini-lecture series for more than three years. The lectures aim to enrich students' knowledge in creative perspectives and arouse their interest in Sciences, Fashion and Textiles. In view of the unpredictable development of the COVID-19 pandemic, the upcoming mini-lecture Series will be switched from face-to-face mode to online mode.
- Subjects:
- Chemistry
- Keywords:
- Forensic sciences Analytical chemistry Crime laboratories
- Resource Type:
- Video