How to Develop a Weighted Average Ensemble for Deep Learning Neural Networks
https://machinelearningmastery.com/weighted-average-ensemble-for-deep-learning-neural-networks/
🔗 How to Develop a Weighted Average Ensemble for Deep Learning Neural Networks
A modeling averaging ensemble combines the prediction from each model equally and often results in better performance on average than a given single model. Sometimes there are very good models that we wish to contribute more to an ensemble prediction, and perhaps less skillful models that may be useful but should contribute less to an …
https://machinelearningmastery.com/weighted-average-ensemble-for-deep-learning-neural-networks/
🔗 How to Develop a Weighted Average Ensemble for Deep Learning Neural Networks
A modeling averaging ensemble combines the prediction from each model equally and often results in better performance on average than a given single model. Sometimes there are very good models that we wish to contribute more to an ensemble prediction, and perhaps less skillful models that may be useful but should contribute less to an …
MachineLearningMastery.com
How to Develop a Weighted Average Ensemble for Deep Learning Neural Networks - MachineLearningMastery.com
A modeling averaging ensemble combines the prediction from each model equally and often results in better performance on average than a given single model.
Sometimes there are very good models that we wish to contribute more to an ensemble prediction,…
Sometimes there are very good models that we wish to contribute more to an ensemble prediction,…
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
New SOTA on cross-lingual transfer (XNLI, MLDoc) and bitext mining (BUCC) using a shared encoder for 93 languages.
Link: https://arxiv.org/abs/1812.10464
#SOTA #NLP
🔗 Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
New SOTA on cross-lingual transfer (XNLI, MLDoc) and bitext mining (BUCC) using a shared encoder for 93 languages.
Link: https://arxiv.org/abs/1812.10464
#SOTA #NLP
🔗 Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
arXiv.org
Massively Multilingual Sentence Embeddings for Zero-Shot...
We introduce an architecture to learn joint multilingual sentence representations for 93 languages, belonging to more than 30 different families and written in 28 different scripts. Our system...
Battling Entropy: Making Order of the Chaos in Our Lives
Article on #entropy as a concept.
Link: https://fs.blog/2018/11/entropy/
🔗 Battling Entropy: Making Order of the Chaos in Our Lives
The second law of thermodynamics says that all things move toward chaos and disorder. Our bodies, our relationships, our businesses. Are we doomed to simply accept it? Maybe not...
Article on #entropy as a concept.
Link: https://fs.blog/2018/11/entropy/
🔗 Battling Entropy: Making Order of the Chaos in Our Lives
The second law of thermodynamics says that all things move toward chaos and disorder. Our bodies, our relationships, our businesses. Are we doomed to simply accept it? Maybe not...
Farnam Street
Entropy: The Hidden Force That Complicates Life
This article will help you learn how Entropy, the second law of thermodynamics, makes life increasingly more complicated. Understanding entroy will supercharge how and where you apply your energy.
Wonderfully interactive, gentle, and well done introduction to probability and statistics. Walk through this with your favorite kid and give them a head-start in life on ML
https://seeing-theory.brown.edu/basic-probability/index.html
🔗 Basic Probability
This chapter is an introduction to the basic concepts of probability theory.
https://seeing-theory.brown.edu/basic-probability/index.html
🔗 Basic Probability
This chapter is an introduction to the basic concepts of probability theory.
seeing-theory.brown.edu
Basic Probability
This chapter is an introduction to the basic concepts of probability theory.
🎥 Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
👁 1 раз ⏳ 2504 сек.
👁 1 раз ⏳ 2504 сек.
Talk slides @ https://qdata.github.io/secureml-web/pic/18Webnar_feature_squeezing-V2.pdf
On December 21 @ 12noon, Dr Qi gave a distinguished webinar talk in the Fall 2018 webinar series of the Institute for Information Infrastructure Protection (I3P) (@ the George Washington University and SRI International).
The recording has small issues in displaying the slides.
More relevant projects are introduced at http://www.securemachinelearning.org/
Vk
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Talk slides @ https://qdata.github.io/secureml-web/pic/18Webnar_feature_squeezing-V2.pdf
On December 21 @ 12noon, Dr Qi gave a distinguished webinar talk in the Fall 2018 webinar series of the Institute for Information Infrastructure Protection (I3P) (@…
On December 21 @ 12noon, Dr Qi gave a distinguished webinar talk in the Fall 2018 webinar series of the Institute for Information Infrastructure Protection (I3P) (@…
Total Least Squares in comparison with OLS and ODR
https://towardsdatascience.com/total-least-squares-in-comparison-with-ols-and-odr-f050ffc1a86a?source=collection_home---4------3---------------------
https://towardsdatascience.com/total-least-squares-in-comparison-with-ols-and-odr-f050ffc1a86a?source=collection_home---4------3---------------------
Towards Data Science
Total Least Squares in comparison with OLS and ODR
The holistic overview of linear regression analysis
https://habr.com/company/ashmanov_net/blog/434712/
Третий Тест Тьюринга на русском языке
#machinelearning #neuralnets #deeplearning #машинноеобучение
Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data
Третий Тест Тьюринга на русском языке
#machinelearning #neuralnets #deeplearning #машинноеобучение
Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data
Habr
Третий Тест Тьюринга на русском языке
Всем привет! Компании «Нейросети Ашманова» и «Наносемантика» приглашают всех желающих принять участие в 3-м всероссийском Тесте Тьюринга в 2019 году, который мы...
Applied Deep Learning with Python Use scikit-learn, TensorFlow, and Keras
📝 Applied Deep Learning with Python Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning... - 💾35 586 419
📝 Applied Deep Learning with Python Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning... - 💾35 586 419
🎥 Can AI Pick Your Next Winning Lottery Number?
👁 2 раз ⏳ 325 сек.
👁 2 раз ⏳ 325 сек.
AI operates based on data. We have years of lottery number data. Can we use it to pick the next number?
What are the characteristics of problems that can be solved by AI and machine learning?
Vk
Can AI Pick Your Next Winning Lottery Number?
AI operates based on data. We have years of lottery number data. Can we use it to pick the next number?
What are the characteristics of problems that can be solved by AI and machine learning?
What are the characteristics of problems that can be solved by AI and machine learning?
On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018
🔗 On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018
On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018 Subscribe Now!
🔗 On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018
On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018 Subscribe Now!
YouTube
On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018
On Optimization And Expressiveness In Deep Learning By Nadav Cohen 2018 Subscribe Now!
How to Develop a Stacking Ensemble for Deep Learning Neural Networks in Python With Keras
https://machinelearningmastery.com/stacking-ensemble-for-deep-learning-neural-networks/
🔗 How to Develop a Stacking Ensemble for Deep Learning Neural Networks in Python With Keras
Model averaging is an ensemble technique where multiple sub-models contribute equally to a combined prediction. Model averaging can be improved by weighting the contributions of each sub-model to the combined prediction by the expected performance of the submodel. This can be extended further by training an entirely new model to learn how to best combine …
https://machinelearningmastery.com/stacking-ensemble-for-deep-learning-neural-networks/
🔗 How to Develop a Stacking Ensemble for Deep Learning Neural Networks in Python With Keras
Model averaging is an ensemble technique where multiple sub-models contribute equally to a combined prediction. Model averaging can be improved by weighting the contributions of each sub-model to the combined prediction by the expected performance of the submodel. This can be extended further by training an entirely new model to learn how to best combine …
MachineLearningMastery.com
Stacking Ensemble for Deep Learning Neural Networks in Python - MachineLearningMastery.com
Model averaging is an ensemble technique where multiple sub-models contribute equally to a combined prediction. Model averaging can be improved by weighting the contributions of each sub-model to the combined prediction by the expected performance of the…
Engineering Lessons Learned by Data Scientists | Data Council NYC '18
https://www.youtube.com/watch?v=Oa1t1GFVwxM
🎥 Engineering Lessons Learned by Data Scientists | Data Council NYC '18
👁 1 раз ⏳ 1842 сек.
https://www.youtube.com/watch?v=Oa1t1GFVwxM
🎥 Engineering Lessons Learned by Data Scientists | Data Council NYC '18
👁 1 раз ⏳ 1842 сек.
ABOUT THE TALK:
MalwareScore is a machine learning based antivirus solution included in Endgame's enterprise security platform. It is fast, lightweight, frequently updated, and has been continually expanded to more and more file types. MalwareScore's journey from Kaggle competition code built in 2015, to brittle proof of concept, to robust production model running on customer workstations contains many twists and turns.
I'll talk about how a small team of data scientists built the original data pipeline a
YouTube
Engineering Lessons Learned by Data Scientists | Endgame
Get the slides: https://www.datacouncil.ai/talks/engineering-lessons-learned-by-data-scientists-in-growing-malwarescore-from-kaggle-competition-to-trusted-antivirus-solution
ABOUT THE TALK:
MalwareScore is a machine learning based antivirus solution included…
ABOUT THE TALK:
MalwareScore is a machine learning based antivirus solution included…
Applying Statistical Modeling and Machine Learning to Perform Time-Series Forecasting
🎥 Applying Statistical Modeling and Machine Learning to Perform Time-Series Forecasting
👁 1 раз ⏳ 5106 сек.
🎥 Applying Statistical Modeling and Machine Learning to Perform Time-Series Forecasting
👁 1 раз ⏳ 5106 сек.
Forecasting time-series data has applications in many fields, including finance, health, etc. There are potential pitfalls when applying classic statistical and machine learning methods to time-series problems. This talk will give folks the basic toolbox to analyze time-series data and perform forecasting using statistical and machine learning models, as well as interpret and convey the outputs.
EVENT:
PyData Los Angeles
SPEAKER:
Tamara Louie
CREDITS:
Original video source: https://www.youtube.com/wat
Vk
Applying Statistical Modeling and Machine Learning to Perform Time-Series Forecasting
Forecasting time-series data has applications in many fields, including finance, health, etc. There are potential pitfalls when applying classic statistical and machine learning methods to time-series problems. This talk will give folks the basic toolbox…
https://habr.com/post/434886/
Разработка аналога FindFace одним школьником
#machinelearning #neuralnets #deeplearning #машинноеобучение
Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data
Разработка аналога FindFace одним школьником
#machinelearning #neuralnets #deeplearning #машинноеобучение
Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data
How to use machine learning for anomaly detection and condition monitoring
https://towardsdatascience.com/how-to-use-machine-learning-for-anomaly-detection-and-condition-monitoring-6742f82900d7?source=collection_home---4------2---------------------
https://towardsdatascience.com/how-to-use-machine-learning-for-anomaly-detection-and-condition-monitoring-6742f82900d7?source=collection_home---4------2---------------------
Towards Data Science
How to use machine learning for anomaly detection and condition monitoring
In this article, I will introduce a couple of different techniques and applications of machine learning and statistical analysis, and then…
Lifelong / Incremental Deep Learning - Ramon Morros - UPC Barcelona 2018
🔗 Lifelong / Incremental Deep Learning - Ramon Morros - UPC Barcelona 2018
https://telecombcn-dl.github.io/2018-dlai/ Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia dat...
🔗 Lifelong / Incremental Deep Learning - Ramon Morros - UPC Barcelona 2018
https://telecombcn-dl.github.io/2018-dlai/ Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia dat...
YouTube
Lifelong / Incremental Deep Learning - Ramon Morros - UPC Barcelona 2018
https://telecombcn-dl.github.io/2018-dlai/ Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia dat...
13. Object Detection: лекция
🔗 13. Object Detection: лекция
В этом видео Илья Захаркин (ФИВТ МФТИ, NeurusLab) расскажет об одном из самых важных применений свёрточных нейросетей -- о детектировании объектов на изображ...
🔗 13. Object Detection: лекция
В этом видео Илья Захаркин (ФИВТ МФТИ, NeurusLab) расскажет об одном из самых важных применений свёрточных нейросетей -- о детектировании объектов на изображ...
YouTube
13. Object Detection: лекция
В этом видео Илья Захаркин (ФИВТ МФТИ, NeurusLab) расскажет об одном из самых важных применений свёрточных нейросетей -- о детектировании объектов на изображениях.
Вы узнаете о датасетах, использующихся для обучения детекторов, познакомитесь с метриками…
Вы узнаете о датасетах, использующихся для обучения детекторов, познакомитесь с метриками…