Neural Networks Part 6: Cross Entropy
When a Neural Network is used for classification, we usually evaluate how well it fits the data with Cross Entropy. This StatQuest gives you and overview of how to calculate Cross Entropy and Total Cross Entropy. NOTE: This StatQuest assumes that you are already familiar with... The main
From playlist StatQuest
Estimation of Coherence and Cross Spectra
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Averaging approaches for estimating coherence and cross spectra, analogous to Welch's averaged periodogram estimator of the power spectrum.
From playlist Estimation and Detection Theory
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
How does cross validation performance change with increase in number of folds K?
#machinelearning #shorts #datascience
From playlist Quick Machine Learning Concepts
AQC 2016 - Towards Quantum Supremacy with Pre-Fault-Tolerant Devices
A Google TechTalk, June 28, 2016, presented by Sergio Boixo (Google) ABSTRACT: A critical question for the field of quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of state-of-th
From playlist Adiabatic Quantum Computing Conference 2016
Covariance (1 of 17) What is Covariance? in Relation to Variance and Correlation
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn the difference between the variance and the covariance. A variance (s^2) is a measure of how spread out the numbers of
From playlist COVARIANCE AND VARIANCE
In this video, we learn a hack to increase the size of our training set while still being able to do validation: cross validation. Link to my notes on Introduction to Data Science: https://github.com/knathanieltucker/data-science-foundations Try answering these comprehension questions to
From playlist Introduction to Data Science - Foundations
We go over ways to implement cross validation, and begin working on neural networks.
From playlist MachineLearning
Supervised Contrastive Learning
The cross-entropy loss has been the default in deep learning for the last few years for supervised learning. This paper proposes a new loss, the supervised contrastive loss, and uses it to pre-train the network in a supervised fashion. The resulting model, when fine-tuned to ImageNet, achi
From playlist General Machine Learning
Deep Learning 2.0: How Bayesian Optimization May Power the Next Generation of DL by Frank Hutter
A Google TechTalk, presented by Frank Hutter, 2022/6/14 ABSTRACT: BayesOpt TechTalk Series. Deep Learning (DL) has been incredibly successful, due to its ability to automatically acquire useful representations from raw data by a joint optimization process of all layers. However, current DL
From playlist Google BayesOpt Speaker Series 2021-2022
Covariance (14 of 17) Covariance Matrix "Normalized" - Correlation Coefficient
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will find the “normalized” matrix (or the correlation coefficients) from the covariance matrix from the previous video using 3 sa
From playlist COVARIANCE AND VARIANCE
Deep Symbolic Regression: Recovering Math Expressions from Data via Risk-Seeking Policy Gradients
The Data Science Institute (DSI) hosted a virtual seminar by Brenden Petersen from Lawrence Livermore National Laboratory on April 22, 2021. Read more about the DSI seminar series at https://data-science.llnl.gov/latest/seminar-series. Discovering the underlying mathematical expressions d
From playlist DSI Virtual Seminar Series
Stanford CS224N: NLP with Deep Learning | Winter 2020 | Low Resource Machine Translation
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3kypBjI Marc'Aurelio Ranzato, Facebook AI Research https://ranzato.github.io/ Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Profess
From playlist Stanford CS224N: Natural Language Processing with Deep Learning Course | Winter 2019
NEW: Multiple Training DATASETS to fine-tune your SBERT model in 2022 (SBERT 33)
Python code on how to train multiple training datasets for your specific Sentence Transformer model. Combine Datasets of SNLI with MS MARCO and Reddit for training your SBERT model. Example on COLAB with PyTorch. #datascience #datastructure #dataset #datasets #pytorch #deeplearning
From playlist Training DATASET for fine-tuning Sentence Transformers SBERT Python
Clojure Conj 2012 - Clojure Data Science
Clojure Data Science by: Edmund Jackson Data science / big data exists at the overlap of traditional analytics and large scale computation. As such, neither the traditional tools of analytics (R, Mathematica, Matlab) nor mainstreams languages (Java, C++, C#) supply its requirements well a
From playlist Clojure Conf 2012
AI Weekly Update - March 15th, 20201 (#28)!
Thank you for watching! Please Subscribe! Content Links: Behavior from the Void: https://arxiv.org/pdf/2103.04551.pdf Barlow Twins: https://arxiv.org/pdf/2103.03230.pdf Pretrained Transformers as Universal Compute Engines: https://arxiv.org/pdf/2103.05247.pdf A New Lens on Understanding G
From playlist AI Research Weekly Updates
Markus Reiher - Uncertainty Quantification of Quantum Chemical Methods - IPAM at UCLA
Recorded 06 May 2022. Markus Reiher ETH Zurich presents "Uncertainty Quantification of Quantum Chemical Methods" at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/workshop-iii-large-scale-certi
From playlist 2022 Large-Scale Certified Numerical Methods in Quantum Mechanics
Estimate the Correlation Coefficient Given a Scatter Plot
This video explains how to estimate the correlation coefficient given a scatter plot.
From playlist Performing Linear Regression and Correlation
Notion Link: https://ebony-scissor-725.notion.site/Henry-AI-Labs-Weekly-Update-July-15th-2021-a68f599395e3428c878dc74c5f0e1124 Chapters 0:00 Introduction 2:18 Improvements in Video Modeling 6:08 Vokenization 7:31 HowTo100M Data 9:07 Teacher Learning 13:06 Interesting Distillation Ideas 17
From playlist AI Weekly Update - July 15th, 2021!