Plan grad entry. Finland’s fighting inequality with education, and winning. What’s their secret? Finland has remade its education system to help kids like Lara Osman – born to poor, immigrant parents – grow up to be middle-class success stories.
Astronomy.swin.edu.au/~cblake/stats.html. Statistics course for PhD students Lectures topic list Cheat sheet / notes Lecture 1 : basic descriptive statistics Lecture 1 - slides [pdf]
How to Time a Presentation. Today I’ll be talking about how to time a presentation.
This is from listener Joe P: What’s the rule for determining how many slides to use in a presentation? Well, like many answers from consultants, my answer is … it depends! How Many Slides to Use in a Presentation? In the past if you asked a presentation skills “pundit” you were likely to hear “one slide per minute,” but times are changing and I don’t think the answer is as simple as a certain number of slides per minute. Again, it depends. Complexity Needs to Be Considered What is important to consider is the complexity of the ideas being presented. In general, you should be able to talk for at least 30 seconds per slide.
Jql_journal.pdf. Writing and presenting your thesis - QUT Students. The advice on this page is just a guide.
Depending on your faculty, type of degree and whether you're studying full-time or part-time, you might not follow these processes exactly. Your supervisor and faculty will guide you through exactly what you need to do. Contact the Research Students Centre if you have any further questions or problems. Types of thesis The thesis guidelines explain the nature and specific requirements of the three types of higher degree research thesis: the Traditional Monographthe Thesis by Published Papersthe Thesis by Creative Works (available in Creative Industries). Formal concept analysis. Formal concept analysis finds practical application in fields including data mining, text mining, machine learning, knowledge management, semantic web, software development, chemistry and biology.
Overview and history
Sparse Distributed Representations: Our Brain's Data Structure. QUT. Cognitive science. Statistics. Neurology. Teaching. Computational Cognitive Science Lab. Like any cognitive scientist, my primary interest is learning how the mind works.
Computational Cognitive Science Lab. I’m interested many different questions in language acquisition and higher-order cognition.
John Pegg. Professor, School of Education Biography Link to further information about Professor Pegg's: Professional journey.
Sonia White. Dr White began her career as a Secondary Mathematics Teacher in Queensland.
Following her interest in educational neuroscience, she completed postgraduate study in the Centre for Neuroscience in Education at the University of Cambridge. Her PhD thesis was entitled ‘The development of number processing skills in Years 1, 2 and 3’. Prior to returning to QUT, Dr White was a research assistant on the European Union (Framework VI) funded project ‘Humans, The Analogy-Making Species’; this was a collaboration with seven EU member institutions. During her time at the University of Cambridge, Sonia was trained in both Electroencephalography (EEG) and Electromyography (EMG) acquisition techniques and associated analysis.
In the Faculty of Education, she completed academic supervision of undergraduate students and was a seminar leader to graduate students for a range of topics related to psychology and education. Sue Walker. Dynamic Notions. A few years ago, I began blogging about Neural Networks.
I have had an interest in this side of machine learning for more time than I can remember. However, even though these amazingly useful constructs have been used to solve many real world problems; they have never really delivered on the dream of a true artificial intelligence – until now. With the advent of Deep Learning algorithms this is all about to change… Neural Networks began as single layer networks that could be used to solve “linearly separable” classification problems. This type of network was known as the perceptron. How Stockfish Works: An Evaluation of the Databases Behind the Top Open-Source Chess Engine. Playing chess has been on the forefront of AI research since Alan Turing and his students proposed chess playing machines.
The game of chess is a domain of human thought where very limited sets of rules yield inexhaustible depths, challenges, frustration and beauty. The playing strategies of AI and human players have diverged proportional to the increase of available computing power, namely speed and storage space. Human players recognize and aim to achieve particular patterns; typically, they perform a deep search weighted towards moves that lead to such desired patterns, transferring past knowledge and adapting it to their present situation.
AI chess is mostly played by parsing through a huge database, with broad search algorithms used to search for the next optimal move. Keywords: Chess, AI Chess, Search Techniques, Chess algorithms, Databases, Alpha-Beta Pruning, Stockfish, Stockfish 2.3.1 Application Domain Design and Schema. How Stockfish Works: An Evaluation of the Databases Behind the Top Open-Source Chess Engine. Zaifrun's Blog. Neural networks and deep learning. The human visual system is one of the wonders of the world.
Artificial Intelligence - foundations of computational agents. Highlights of Calculus. Linear Algebra. Lecture 1: The geometry of linear equations. A First Course in Linear Algebra (A Free Textbook) Streeter-2008-Brain-Inspired-AGI-poster.png (PNG Image, 1800 × 1200 pixels) - Scaled (56%) Adelaide. R. Lecturers. Cognitive modelling. Bayesian.