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  • Courseware 
    CS50’s Introduction to Artificial Intelligence with Python

    CS50’s Introduction to Artificial Intelligence with Python

    This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.

    Course related:
    COMP3011 Design and Analysis of Algorithms, COMP1001 Problem Solving Methodology in Information Technology, COMP4434 Artificial Intelligence, and COMP2011 Data Structures
    Subjects:
    Human-Computer Interaction and Computing
    Keywords:
    Computer programming Computer science Python (Computer program language) Artificial intelligence
    Resource Type:
    Courseware
     
  • MOOC 
    Machine Learning Specialization

    Machine Learning Specialization

    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
     
  • Others 
    Kaggle

    Kaggle

    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
     
  • Others 
    OER

    Deep Learning in GeoSpatial Artificial Intelligence

    Geospatial artificial intelligence sometimes referred to as geoAI is recently receiving so much attention. From large-scale projects to smaller projects. GeoAI can be referred to as using artificial intelligence with Geographical information system to analyse and produce solution-based predictions.

    Subjects:
    Computing and Land Surveying and Geo-Informatics
    Keywords:
    Geospatial data Geographic information systems Artificial intelligence
    Resource Type:
    Others
     
  • Others 
    Agile Software Development: It’s Implication for AI products and Developers

    Agile Software Development: It’s Implication for AI products and Developers

    Software developments is advancing the technological world today. This changes have far more reaching implications in I.T industries such as Big data, Artificial intelligence and Agile Software development methodologies. Competition in the software development ecosystem has made developers to build software that are quick and reliable and often referred to as Agile development. Agile transformation is real and requires rethinking the business management, recruitment process and data strategy in a bid to stimulate disruptive solutions from within in-house development and deployment. AI product development would require rapid transformational changes within any organization. This can be accomplished by establishing specific operating models that permit development teams with the freedom of technology choice. This publication highlights some operating models that can be adopted to improve the success of AI products using Agile software development methodologies.

    Subjects:
    Computing
    Keywords:
    Agile software development
    Resource Type:
    Others
     
  • Courseware 
    CS229 - Machine Learning

    CS229 - Machine Learning

    This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.

    Subjects:
    Computing
    Keywords:
    Pattern perception -- Statistical methods Machine learning
    Resource Type:
    Courseware
     
  • e-book 
    Evolutionary Algorithms

    Evolutionary Algorithms

    Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on. Apart from mathematical optimization problems, evolutionary algorithms have also been used as an experimental framework within biological evolution and natural selection in the field of artificial life.

    Subjects:
    Computing
    Keywords:
    Mathematical optimization Genetic algorithms Evolutionary programming (Computer science)
    Resource Type:
    e-book
     
  • e-book 
    Artificial Intelligence

    Artificial Intelligence

    Artificial intelligence (AI) is a potent buzzword and happening technology which has greatly impacted the lifestyle of every human being either directly or indirectly and is shaping the future of tomorrow. In fact, AI is fast becoming an intrinsic part of our daily life and is not confined to university research labs, even if remarkable progress has been made in this domain. The benefit of this phenomenon is widely recognized in diversified areas, ranging from medicine to security to consumer applications and business, and resulting in improvements in the quality of life of humankind. Every new disruptive technology has its own pros and cons and AI is no exception to this rule. Privacy, data protection, and the rights of individuals pose social and ethical challenges.

    Subjects:
    Computing
    Keywords:
    Artificial intelligence
    Resource Type:
    e-book
     
  • Presentation 
    Media Stream

    Media Stream

    This video was recorded at COIN / PlanetData Winter School on Knowledge Technologies for Complex Business Environments, Ljubljana 2011. Organized by COIN FP7 Integrated Project and PlanetData FP7 Network of Excellence, the school seeks to bring together students, scholars and researchers from industry in order to foster collaboration and interoperability with innovative services and project large-scale data management in business environments. The main topics of the winter school are: Interoperability and collaboration models and solutions, Enterprise interoperability and collaboration services, Innovative knowledge and semantically powered technologies, Knowledge process and context modelling, Pro-active knowledge tools, Large scale analytics and reasoning tools, Business cases and real case studies. Detailed information can be found here.

    Subjects:
    Management and Computing
    Keywords:
    Data mining Real-time data processing
    Resource Type:
    Presentation
     
    OER
  • Presentation 
    Logic-based ad-hoc business process management: Concepts and challenges

    Logic-based ad-hoc business process management: Concepts and challenges

    This video was recorded at 7th Extended Semantic Web Conference (ESWC), Heraklion 2010. The mission of the Extended Semantic Web Conference (ESWC 2010) is to bring together researchers and practioners dealing with different aspects of semantics on the Web. ESWC2010 builds on the success of the former European Semantic Web Conference series, but seeks to extend its focus by engaging with other communities within and outside ICT, in which semantics can play an important role. At the same time, ESWC2010 is a truly international conference. Semantics of web content, enriched with domain theories (ontologies), data about web usage, natural language processing, etc. will enable a web that provides a qualitatively new level of functionality. It will weave together a large network of human knowledge and make this knowledge machine-processable. Various automated services, based on reasoning with metadata and ontologies, will help the users to achieve their goals by accessing and processing information in machine-understandable form. This network of knowledge systems will ultimately lead to truly intelligent systems, which will be employed for various complex decision-making tasks. Research about web semantics can benefit from ideas and cross-fertilization with many other areas: Artificial Intelligence, Natural Language Processing, Database and Information Systems, Information Retrieval, Multimedia, Distributed Systems, Social Networks, Web Engineering, and Web Science. ESWC2010 will present the latest results in research and applications in its field. The research program will be organised in targeted tracks. In addition, the conference will feature a tutorial program, system descriptions and demos, a posters track, a Ph.D. symposium and a number of collocated workshops. The calls for these events are separate and can be found on the conference Web site (http://www.eswc2010.org/).

    Subjects:
    Management and Computing
    Keywords:
    Industrial management Workflow -- Management
    Resource Type:
    Presentation
     
    OER