In linear regression, mean response and predicted response are values of the dependent variable calculated from the regression parameters and a given value of the independent variable. The values of these two responses are the same, but their calculated variances are different. (Wikipedia).
The Normal Distribution (1 of 3: Introductory definition)
More resources available at www.misterwootube.com
From playlist The Normal Distribution
(ML 7.7.A2) Expectation of a Dirichlet random variable
How to compute the expected value of a Dirichlet distributed random variable.
From playlist Machine Learning
This video explains how to determine mean, median and mode. It also provided examples. http://mathispower4u.yolasite.com/
From playlist Statistics: Describing Data
Find the Expected Value (Mean) for a Discrete Random Variable Prob Dist - Partial Table
This video explains how to determine the expected value (mean) given a discrete random variable probability distribution.
From playlist Discrete Random Variables
More resources available at www.misterwootube.com
From playlist Relative Frequency and Probability
Statistics 5_1 Confidence Intervals
In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.
From playlist Medical Statistics
(PP 4.1) Expectation for discrete random variables
(0:00) Definition of expectation for discrete r.v.s. (4:17) Well-defined expectation. (8:15) E(X) may exist and be infinite. (10:58) E(X) might fail to exist. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5DB5E4
From playlist Probability Theory
Discrete Random Variables (1 of 3: Expected value & median)
More resources available at www.misterwootube.com
From playlist Probability and Discrete Probability Distributions
Neuronal Signals for Economic Utility - W. Schultz - 6/1/17
T & C Chen Center for Social and Decision Neuroscience Distinguished Lecture “Neuronal Signals for Economic Utility” Wolfram Schultz, Professor of Neuroscience, University of Cambridge Wolfram Schultz works on the biological basis of reward. He uses behavioral concepts from animal learni
From playlist Talks and Seminars
Comparing machine learning models in scikit-learn
We've learned how to train different machine learning models and make predictions, but how do we actually choose which model is "best"? We'll cover the train/test split process for model evaluation, which allows you to avoid "overfitting" by estimating how well a model is likely to perform
From playlist Machine learning in Python with scikit-learn
Lecture4. Customer relationship management. Churn prediction.Classification.
Data Science for Business. Lecture 4 slides: https://drive.google.com/file/d/1J_Ufp6MtMQp_L2JI3nh9xQYsu6LDEdm8/view?usp=sharing
From playlist Data Science for Business, 2022
Training a machine learning model with scikit-learn
Now that we're familiar with the famous iris dataset, let's actually use a classification model in scikit-learn to predict the species of an iris! We'll learn how the K-nearest neighbors (KNN) model works, and then walk through the four steps for model training and prediction in scikit-lea
From playlist Machine learning in Python with scikit-learn
How to evaluate a classifier in scikit-learn
In this video, you'll learn how to properly evaluate a classification model using a variety of common tools and metrics, as well as how to adjust the performance of a classifier to best match your business objectives. I'll start by demonstrating the weaknesses of classification accuracy as
From playlist Machine learning in Python with scikit-learn
Simple Linear Regression (Part E)
Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics
R & Python - Linear Regression
Lecturer: Dr. Erin M. Buchanan Summer 2020 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class - this video set covers the updated version with both R and Python. Regression is a popular technique for continuous data - in this example, we talk
From playlist Human Language (ANLY 540)
Pedro Ballester: Precision and recall oncology: combining multiple gene mutations for...
Abstract: Cancer patients often respond differently to the same treatment. Precision oncology aims at predicting which treatments will be effective on a given patient. Such predictive biomarkers of drug response typically take the form of a particular somatic mutation. However, lessons fro
From playlist Mathematics in Science & Technology
Nonlinear Dynamics of Complex Systems:
Multi-Dimensional Time Series, Network Inference and Nonequilibrium Tipping - by Prof. Marc Timme - Lecture IV
From playlist Networked Complexity
Expected Value of a Discrete Probability Distribution
This video explains how to determine the expected value or mean value of a discrete probability distribution. http://mathispower4u.com
From playlist Probability
Kaggle Reading Group: Learning from Dialogue after Deployment (Part 2) | Kaggle
This week we continue with the paper "Learning from Dialogue after Deployment: Feed Yourself, Chatbot!" by Hancock et al, 2019. (Published at ACL 2019 in Venice.) Link to paper: https://www.aclweb.org/anthology/P19-1358.pdf About Kaggle: Kaggle is the world's largest community of data sc
From playlist Kaggle Reading Group | Kaggle