Pattern Matching - Correctness
Learn how to use pattern matching to assist you in your determination of correctness. This video contains two examples, one with feedback and one without. https://teacher.desmos.com/activitybuilder/custom/6066725595e2513dc3958333
From playlist Pattern Matching with Computation Layer
Predicting outcomes with Pattern Recognition: Machine Learning for Algorithmic Trading p. 8
Using previous pattern outcomes to help us begin to predict future outcomes. Welcome to the Machine Learning for Forex and Stock analysis and automated trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field
From playlist Machine Learning for Forex and Stock analysis and algorithmic trading.
Pattern Recognition: Machine Learning for Algorithmic Trading Part 9
Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. This is especially useful for people interested in q
From playlist Machine Learning for Forex and Stock analysis and algorithmic trading.
Variables in Pattern Recognition: Machine Learning for Algorithmic Trading in Forex and Stocks p. 13
This video discusses the already many variables that need to be considered in our pattern recognition and how we use it. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning
From playlist Machine Learning for Forex and Stock analysis and algorithmic trading.
Sometimes you need to nest a pattern in another pattern. Learn how to build these patterns and then extract information from them. https://teacher.desmos.com/activitybuilder/custom/605e21d90925ca0c93fabbbd
From playlist Pattern Matching with Computation Layer
Image Recognition and Python Part 1
Sample code for this series: http://pythonprogramming.net/image-recognition-python/ There are many applications for image recognition. One of the largest that people are most familiar with would be facial recognition, which is the art of matching faces in pictures to identities. Image rec
From playlist Image Recognition
Pattern Recognition and Outcome: Machine Learning for Algorithmic Trading in Forex and Stocks
Here, we are beginning to compile the past historical patterns that we are comparing to, and taking their eventual outcome for use in future predictions. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taugh
From playlist Machine Learning for Forex and Stock analysis and algorithmic trading.
Image Recognition and Python Part 4
This is the fourth video to my image recognition basics series. Image recognition can be used for all sorts of things like facial recognition, identifying what is in pictures, character recognition, and more. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
From playlist Image Recognition
Lecture 2.3: Josh Tenenbaum - Computational Cognitive Science Part 3
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Josh Tenenbaum Exploring how humans learn new concepts and make intelligent inferences from little experience. Using probabilistic generative models
From playlist MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015
Lecture 13/16 : Stacking RBMs to make Deep Belief Nets
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 13A The ups and downs of backpropagation 13B Belief Nets 13C Learning Sigmoid Belief Nets 13D The wake-sleep algorithm
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]
Lecture 2.1: Josh Tenenbaum - Computational Cognitive Science Part 1
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Josh Tenenbaum Exploring how humans learn new concepts and make intelligent inferences from little experience. Using probabilistic generative models
From playlist MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015
Lecture 7.5: Hynek Hermansky - Auditory Perception in Speech Technology, Part 2
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Hynek Hermansky Integrating insights from human auditory perception and speech generation into the development of speech production and recognition t
From playlist MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015
Sparks! Interview of Caltech professor, Anima ANANDKUMAR on the status of AI today!
Caltech professor, Anima ANANDKUMAR on the status of AI today Anima Anandkumar, Bren professor at Caltech and a director of machine learning research at NVIDIA presents the current breakthroughs in the status of AI research today, and its potential contribution to scientific discovery
From playlist Sparks! Serendipity Forum at CERN | Launch Event | 2020
Lecture 7.4: Hynek Hermansky - Auditory Perception in Speech Technology, Part 1
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Hynek Hermansky Integrating insights from human auditory perception and speech generation into the development of speech production and recognition t
From playlist MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015
Pattern Finding and Storing: Machine Learning for Algorithmic Trading in Forex and Stocks Part 6
In this video, we are finding and storing patterns to be later used in the pattern recognition. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition pr
From playlist Machine Learning for Forex and Stock analysis and algorithmic trading.
DeepMind x UCL | Deep Learning Lectures | 3/12 | Convolutional Neural Networks for Image Recognition
In the past decade, convolutional neural networks have revolutionised computer vision. In this lecture, DeepMind Research Scientist Sander Dieleman takes a closer look at convolutional network architectures through several case studies, ranging from the early 90's to the current state of t
From playlist Learning resources
Bias in Algorithms, Nisheeth Vishnoi - Moderated Conversation with Aleksander Mądry
Artificial algorithms are increasingly being deployed to inform, endorse, and govern various aspects of today’s society. Their reach includes the domains of hiring, lending, medicine, criminal justice, insurance, allocation of public services, social and business interactions, and the dis
From playlist Franke Program in Science and the Humanities
Sparks! Serendipity Forum at CERN: Future Intelligence - Full launch event
Sparks! The Serendipity Forum at CERN is a new multi-annual multidisciplinary science innovation initiative from CERN, the European particle physics lab in Geneva. This is the launch of Sparks!, on 26 November 2020: a discussion of the state of artificial intelligence and how it intersec
From playlist Sparks! Serendipity Forum at CERN | Launch Event | 2020
Isabelle Bloch - Hybrid AI for Knowledge Representation and Model-based Image Understanding - (...)
This presentation will focus on hybrid AI, as a step towards explainability, more specifically in the domain of spatial reasoning and image understanding. Image understanding benefits from the modeling of knowledge about both the scene observed and the objects it contains as well as their
From playlist 8th edition of the Statistics & Computer Science Day for Data Science in Paris-Saclay, 9 March 2023
Past outcomes as predictions: Machine Learning for Automated Trading in Forex and Stocks p. 14
Using past outcomes as predictions from our pattern recognition. Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stock
From playlist Machine Learning for Forex and Stock analysis and algorithmic trading.