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
(ML 11.4) Choosing a decision rule - Bayesian and frequentist
Choosing a decision rule, from Bayesian and frequentist perspectives. To make the problem well-defined from the frequentist perspective, some additional guiding principle is introduced such as unbiasedness, minimax, or invariance.
From playlist Machine Learning
Machine learning describes computer systems that are able to automatically perform tasks based on data. A machine learning system takes data as input and produces an approach or solution to a task as output, without the need for human intervention. Machine learning is closely tied to th
From playlist Data Science Dictionary
In this video, you’ll learn more about the evolution of machine learning and its impact on daily life. Visit https://www.gcflearnfree.org/thenow/what-is-machine-learning/1/ for our text-based lesson. This video includes information on: • How machine learning works • How machine learning i
From playlist Machine Learning
(ML 11.8) Bayesian decision theory
Choosing an optimal decision rule under a Bayesian model. An informal discussion of Bayes rules, generalized Bayes rules, and the complete class theorems.
From playlist Machine Learning
What Is Supervised Learning In Machine Learning? | Machine Learning For Beginners | Simplilearn
This video on What is Supervised Learning in machine learning will take you through a detailed concept of Supervised Learning. This video will help you to understand What is Machine Learning, what is supervised learning, how supervised learning works, the advantages and disadvantages of su
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
(ML 11.2) Decision theory terminology in different contexts
Comparison of decision theory terminology and notation in three different contexts: in general, for estimators, and for regression/classification.
From playlist Machine Learning
Introduction To Machine Learning | Machine Learning Basics for Beginners | ML Basics | Simplilearn
Machine Learning is a trending topic nowadays. This Introduction to Machine Learning video will help you to understand what is Machine Learning, importance of Machine Learning, advantages and disadvantages of Machine Learning, what are the types of Machine Learning - supervised, unsupervis
Playing By the Rules-Based Systems || Vincent Warmerdam
Back in the old days, it was common to write rule-based systems. Systems that do; data - [rules] -labels. Nowadays, it's much more fashionable to use machine learning instead. Something like; (labels, data) - [model] - rules. It might be a good time to ask ourselves, is this a better app
From playlist Machine Learning
Apriori Algorithm | Apriori Algorithm In Machine Learning | Association Rule Mining | Simplilearn
Apriori algorithm is a popular machine learning technique used for building recommendation systems. This video will make you understand what recommender systems are and how it works. You will also learn about collaborative filtering and association rule mining. Finally, you will get an ide
A Quest for Visual Intelligence in Computers | Fei-Fei Li | WiDS 2017
It takes nature and evolution more than five hundred million years to develop a powerful visual system in humans. The journey for AI and computer vision is about fifty years. In this talk, I will briefly discuss the key ideas and the cutting edge advances in the quest for visual intelligen
From playlist Women in Data Science (WiDS)
A Literature Review on Machine Learning in Materials Science | AISC
For slides and more information on the paper, visit https://aisc.ai.science/events/2020-04-28-lit-survey-ml-materials-science Discussion lead: Shahrzad Hosseini
From playlist Literature Review
Boosting Machine Learning Tutorial | Adaptive Boosting, Gradient Boosting, XGBoost | Edureka
** Machine Learning Certification Training using Python: https://www.edureka.co/python ** This Edureka session will help you understand all about Boosting Machine Learning and boosting algorithms and how they can be implemented to increase the efficiency of Machine Learning models. The fol
From playlist Machine Learning Algorithms in Python (With Demo) | Edureka
Rasa Algorithm Whiteboard - RulePolicy
In the age of deep learning and transformers, rule-based systems can still be a great idea. In this video, we hope to demonstrate why while we highlight a new feature of Rasa 2.0: the RulePolicy.
From playlist Algorithm Whiteboard
DeepSec 2011: Behavioral Security: 10 steps forward 5 steps backward
Speaker: Sourabh Satish Sourabh Satish explores the approach to behavioural security and talked about it at the DeepSec 2011 security conference: "Rule-based behavioral security has been talked about for decades BUT is it really the silver bullet solution to the malware problem? We don't
From playlist DeepSec 2011
Conversational AI with Rasa: Pipeline and Policy Configuration
In this episode of Conversational AI with Rasa, Justina Petraitytė will cover how to fine tune your Rasa chatbot by changing your NLU pipelines and policy components. Learn more about Rasa: https://rasa.com Rasa documentation: http://rasa.com/docs Join the Rasa Community: https://forum.ra
From playlist Conversational AI with Rasa Open Source 3.x
During this session, mathematician, software engineer and data scientist Luis Serrano provided a primer on machine learning, breaking down the basics and providing examples of real world successes in practice. Following his presentation, Serrano and TIG's Brian Wyman discussed machine lear
From playlist ML Talks by Luis Serrano
Explaining generalisation and individual justice, Reuben Binns
- Links to talks - Reuben Binns: https://youtu.be/VoPSvQYeYpI Alison Reuben: https://youtu.be/btUxLhTPvUQ David Leslie: https://youtu.be/F4G0_01kAN4 Panel discussion: https://youtu.be/WM8BmRkIXX0 In the lecture series 'Driving data futures', the public policy programme of The Alan Turing
From playlist Driving Data Futures: AI explainability with a human face
This lecture gives an overview of the main categories of machine learning, including supervised, un-supervised, and semi-supervised techniques, depending on the availability of expert labels. We also discuss the different methods to handle discrete versus continuous labels. Book websit
From playlist Intro to Data Science