Learning classifier system

Introduction to Classification Models

Ever wonder what classification models do? In this quick introduction, we talk about what classifications models are, as well as what they are used for in machine learning. In machine learning there are many different types of models, all with different types of outcomes. When it comes t

From playlist Introduction to Machine Learning

Training Your Logistic Classifier

This video is part of the Udacity course "Deep Learning". Watch the full course at https://www.udacity.com/course/ud730

From playlist Deep Learning | Udacity

Let's make a deal

This video is part of the Udacity course "Deep Learning". Watch the full course at https://www.udacity.com/course/ud730

From playlist Deep Learning | Udacity

Introduction (3): Supervised Learning

Basics of supervised learning; regression, classification

From playlist cs273a

Machine Learning

If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.

From playlist Machine Learning

Digging into Data: Supervised Classification with Decision Trees

Our second classification lecture, where we cover non-linear decision trees.

From playlist Digging into Data

Supervised Classification

This video is part of the Udacity course "Deep Learning". Watch the full course at https://www.udacity.com/course/ud730

From playlist Deep Learning | Udacity

Everything you need to know about Machine Learning!

Here is an introduction to Machine Learning. Instead of developing algorithms for every task and subtask to solve a problem, Machine Learning involves teaching a computer to teach itself. There are different types of machine learning problems we may come across. TYPES OF MACHINE LEARNING

From playlist Algorithms and Concepts

An Introduction to Classification

Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Develop predictive models for classifying data. For more videos, visit http://www.mathworks.com/products/statistics/examples.html

From playlist Math, Statistics, and Optimization

Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 16 - Social & Ethical Considerations

For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/31ejtX7 To learn more about this course visit: https://online.stanford.edu/courses/cs224n-natural-language-processing-deep-learning To follow along with the course

From playlist Stanford CS224N: Natural Language Processing with Deep Learning | Winter 2021

Dynamical Systems as Feature Representations for Learning from Data - Peter Tino - 6/25/2019

AstroInformatics 2019 Conference: AstroInformatics Methods and Applications http://astroinformatics2019.org/

From playlist AstroInformatics 2019 Conference

Loan Approval Prediction using Machine Learning | Machine Learning Projects 2022 | Simplilearn

In this video, we are going to cover how to implement a loan approval prediction system using Python. This video will help you to understand what is a loan approval prediction system, after which will do a hands-on lab demo to implement a loan approval prediction system using python. ⏺ L

From playlist 🔥Machine Learning | Machine Learning Tutorial For Beginners | Machine Learning Projects | Simplilearn | Updated Machine Learning Playlist 2023

Real World Active Learning - Machine Learning

Originally aired on August 21, 2014. Machine learning research is often not applied to real world situations. Often the improvements are small and the increased complexity is high, so except in special situations, industry doesn't take advantage of advances in the academic literature. Ac

From playlist O'Reilly Webcasts 3

Lecture 15 - Validating Models

This is Lecture 15 of the CSE519 (Data Science) course taught by Professor Steven Skiena [http://www.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: http://www.cs.stonybrook.edu/~skiena/519 More information may be found here: http://www

From playlist CSE519 - Data Science Fall 2016

Building the Automated Data Scientist: The New Classify and Predict

To learn more about Wolfram Technology Conference, please visit: https://www.wolfram.com/events/technology-conference/ Speaker: Etienne Bernard Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, a

From playlist Wolfram Technology Conference 2017

Precision, Recall & F-Measure

In this video, we discuss performance measures for Classification problems in Machine Learning: Simple Accuracy Measure, Precision, Recall, and the F (beta)-Measure. We explain the concepts in detail, highlighting differences between the terms, introducing Confusion Matrices, and analyzi

From playlist Algorithms and Concepts

Stanford Seminar - Crowdsourcing for Machine Learning

Dan Weld University of Washington Dynamic professionals sharing their industry experience and cutting edge research within the human-computer interaction (HCI) field will be presented in this seminar. Each week, a unique collection of technologists, artists, designers, and activists will

From playlist Stanford Seminars

Shortcut Learning in Deep Neural Networks

This paper establishes a framework for looking at out-of-distribution generalization failures of modern deep learning as the models learning false shortcuts that are present in the training data. The paper characterizes why and when shortcut learning can happen and gives recommendations fo

From playlist Adversarial Examples

IAML8.12 Evaluating classification and regression

From playlist Generalization and Evaluation

Natural Language Processing Template Engine

In this presentation we discuss the completion of computational templates with parameters that are extracted from text specifications using a question answering system (QAS) [Wk1]. We outline the general method and then demonstrate it with several types of computational workflows: classifi

From playlist Wolfram Technology Conference 2022