Undersampling

Underactive thyroid.mov

An general explanation of the underactive thyroid.

From playlist For Patients

IAML8.3 Examples of overfitting and underfitting

From playlist Generalization and Evaluation

IAML8.2 Overfitting and underfitting

From playlist Generalization and Evaluation

IDEspinner Buffer Overflows pt1

This movie tries to show how you can create a bufferoverflow Credits go out to IDEspinner

From playlist Buffer overflow

Is the Curse of Dimensionality the same as overfitting?

#machinelearning #shorts #datascience

From playlist Quick Machine Learning Concepts

Outtakes

Yes. I make mistakes ... rarely. http://www.flippingphysics.com

From playlist Miscellaneous

Machine Learning with Imbalanced Data -Part 4 (Undersampling, Clustering-Based Prototype Generation)

In this video, we discuss under-sampling techniques for learning from imbalanced data sets, including random sampling and clustering-based prototype generation. We also see how to implement these techniques using NumPy, Scikit-learn, and Imbalanced-learn in Python. We notice that the proto

From playlist Machine Learning with Imbalanced Data - Dr. Data Science Series

Linear regression (5): Bias and variance

Inductive bias; variance; relationship to over- & under-fitting

From playlist cs273a

Applied ML 2020 - 10 - Calibration, Imbalanced data

Class materials at https://www.cs.columbia.edu/~amueller/comsw4995s20/schedule/

From playlist Applied Machine Learning 2020

Never Gonna Hit Those Notes

From playlist Songs to Torture Undergrads

Applied Machine Learning 2019 - Lecture 11 - Imbalanced data

Undersampling, oversampling, SMOTE, Easy Ensembles Class website with slides and more materials: https://www.cs.columbia.edu/~amueller/comsw4995s19/schedule/

From playlist Applied Machine Learning - Spring 2019

Daniel Rueckert: "Deep learning in medical imaging"

New Deep Learning Techniques 2018 "Deep learning in medical imaging: Techniques for image reconstruction, super-resolution and segmentation" Daniel Rueckert, Imperial College London Abstract: This talk will introduce framework for reconstructing MR images from undersampled data using a d

From playlist New Deep Learning Techniques 2018

Buffer Overflow No ASLR

From playlist Buffer overflow

Machine Learning with Imbalanced Data - Part 5 (Ensemble learning, Bagging classifier)

In this video, we discuss the use of ensemble learning strategies to address the class imbalance problem. Therefore, one can use a combination of data-level preprocessing methods and cost-sensitive learning to improve the performance of classifiers on class-imbalanced data sets. #Imbalan

From playlist Machine Learning with Imbalanced Data - Dr. Data Science Series

Undersampling Gone Wrong - Data Scientist Reacts Ep. 51

Nick Wan is the Director of Analytics for the Cincinnati Reds. He streams data science on Twitch and reacts to the latest news, sports, memes and everything in between. Twitter: https://twitter.com/nickwan WATCH LIVE ON TWITCH: https://twitch.tv/nickwan_datasci https://twitch.tv/nickwan

From playlist Data Scientist Reacts

Machine Learning with Imbalanced Data - Part 3 (Over-sampling, SMOTE, and Imbalanced-learn)

In this video, we discuss the class imbalance problem and how to use over-sampling methods to address this problem. We use the thyroid data set and the logistic regression classifier to train binary classifiers on the original data set and the preprocessed data. We discuss uniform sampling

From playlist Machine Learning with Imbalanced Data - Dr. Data Science Series

時系列 (Time Series)

Mathematica 10の新しい時系列関数を扱います． → 最新情報はこちらでご覧ください： http://www.wolfram.com →　ノートブックはこちらからダウンロードできます： http://www.wolfram.com/training/special-event/virtual-conference-japan-2015/resources.html

From playlist Wolfram Virtual Conference Japan 2015 (Japanese)

Daniel Rueckert: "Deep learning and shape modelling for medical image reconstruction, segmentati..."

Deep Learning and Medical Applications 2020 "Deep learning and shape modelling for medical image reconstruction, segmentation and analysis" Daniel Rueckert, Imperial College London Abstract: This talk will discuss deep learning approaches for the reconstruction, super-resolution and segm

From playlist Deep Learning and Medical Applications 2020

David Corliss: Bayesian capture-recapture in social justice research

Abstract: Capture-Recapture (RC) methodology provides a way to estimate the size of a population from multiple, independent samples. While the was developed more than a century ago to count animal populations, it has only recently become important in Data For Social Good. The large number

From playlist Probability and Statistics

Engine over run - Basics

This video explains about the basics of engine over run. A detailed video animation will be uploaded later. As you all know, the engine has a limited maximum speed at which it operates. But if we abuse the vehicle, the engine speed rises beyond the limited maximum speed. This phenomenon

From playlist Automobile Engineering.