​Protobuf for NVIDIA Jetson
How to deploy a protobuf model from AutoML Vision with Python on a NVIDIA Jetson

https://medium.com/ri-rewe-digital/protobuf-for-nvidia-jetson-e8b2c6ee47cc?source=topic_page---------0------------------1

🔗 Deploy AutoML protobuf model on NVIDIA Jetson
How to deploy a protobuf model from AutoML Vision with Python on a NVIDIA Jetson

🎥 Support vector machines (machine learning ) in R
👁 1 раз ⏳ 532 сек.
I have explained how to perform support vector machine classifier in machine learning using R

​Seeing is Believing — Mesoscopic Neural Networks for Synthetic Image Detection: an Implementation in

🔗 Seeing is Believing — Mesoscopic Neural Networks for Synthetic Image Detection: an Implementation in
Inception layer-powered intermediate detail level recognition

​📝 Rashid_Sozdaem_neyronnuyu_set.djvu - 💾2 935 222

🎥 24x7 AI - Machine Learning - Data Science Tutorials by World's Best Instructors
👁 5 раз ⏳ 42760 сек.
Collection of besr tutorials in the field of Data Science - played 24x7 - Learn Machine Learning and Artificial Intelligence whenever you can - Just tune in this live Data Science Station

​AI Learns To Animate Your Face in VR

Paper:https://research.fb.com/publications/vr-facial-animation-via-multiview-image-translation/

video: https://www.youtube.com/watch?v=hkSfHCtpnHU

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🎥 AI Learns To Animate Your Face in VR
👁 1 раз ⏳ 243 сек.
❤️ Check out Linode here and get $20 free on your account:
https://www.linode.com/papers

📝 The paper "VR Facial Animation via Multiview Image Translation" is available here:
https://research.fb.com/publications/vr-facial-animation-via-multiview-image-translation/

🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
313V, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Anthony Vdovitchenko, Brian Gilman, Bruno Brito, Bryan Learn, Christian Ahlin, Christoph Jadanows

​Bayesian Deep Learning Benchmarks

https://github.com/OATML/bdl-benchmarks

🔗 OATML/bdl-benchmarks
Bayesian Deep Learning Benchmarks. Contribute to OATML/bdl-benchmarks development by creating an account on GitHub.

​TensorFlow with Apache Arrow Datasets

Apache Arrow enables the means for high-performance data exchange with TensorFlow that is both standardized and optimized for analytics and machine learning. The Arrow datasets from TensorFlow I/O provide a way to bring Arrow data directly into TensorFlow tf.data that will work with existing input pipelines and tf.data.Dataset APIs.

https://medium.com/tensorflow/tensorflow-with-apache-arrow-datasets-cdbcfe80a59f

🔗 TensorFlow with Apache Arrow Datasets
An Overview of Apache Arrow Datasets Plus Example To Run Keras Model Training

​U-Net Training with Instance-Layer Normalization
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
Authors: Xiao-Yun Zhou, Qing-Biao Li, Mali Shen, Peichao Li, Zhao-Yang Wang, Guang-Zhong Yang

Abstract: Normalization layers are essential in a Deep Convolutional Neural Network (DCNN). Various normalization methods have been proposed. The statistics used to normalize the feature maps can be computed at batch, channel, or instance level. However, in most of existing methods, the normalization for each layer is fixed
https://arxiv.org/abs/1908.08466

🔗 U-Net Training with Instance-Layer Normalization
Normalization layers are essential in a Deep Convolutional Neural Network (DCNN). Various normalization methods have been proposed. The statistics used to normalize the feature maps can be computed at batch, channel, or instance level. However, in most of existing methods, the normalization for each layer is fixed. Batch-Instance Normalization (BIN) is one of the first proposed methods that combines two different normalization methods and achieve diverse normalization for different layers. However, two potential issues exist in BIN: first, the Clip function is not differentiable at input values of 0 and 1; second, the combined feature map is not with a normalized distribution which is harmful for signal propagation in DCNN. In this paper, an Instance-Layer Normalization (ILN) layer is proposed by using the Sigmoid function for the feature map combination, and cascading group normalization. The performance of ILN is validated on image segmentation of the Right Ventricle (RV) and Left Ventricle (LV) using U-Net

​The Poisson Process: Everything you need to know
Learn about the Poisson process and how to simulate it using Python

https://towardsdatascience.com/the-poisson-process-everything-you-need-to-know-322aa0ab9e9a?source=collection_home---4------2-----------------------

🔗 The Poisson Process: Everything you need to know
Learn about the Poisson process and how to simulate it using Python

​What is the difference between Optimization and Deep Learning and why should you care
Deep Learning is not just Optimization and we need to do something about it
https://towardsdatascience.com/what-is-the-difference-between-optimization-and-deep-learning-and-why-should-you-care-e4dc7c2494fe?source=collection_home---4------0-----------------------

🔗 What is the difference between Optimization and Deep Learning and why should you care
Deep Learning is not just Optimization and we need to do something about it

​A New Consciousness of Inclusion in Machine Learning
http://blog.shakirm.com/2019/06/a-new-consciousness-of-inclusion-in-machine-learning/

🔗 A New Consciousness of Inclusion in Machine Learning
On LGBT Freedoms and our Support for Machine Learning in Africa This is an exploration of my thinking and my personal views. Read in · 1147 words · Soon, in two neighbouring countries in Africa, tw…

🎥 Industrialized Capsule Net for Text Analytics by Dr. Vijay Agneeswaran & Abhishek Kumar #ODSC_India
👁 1 раз ⏳ 2683 сек.
Multi-label text classification is an interesting problem where multiple tags or categories may have to be associated with the given text/documents. Multi-label text classification occurs in numerous real-world scenarios, for instance, in news categorization and in bioinformatics (gene classification problem, see [Zafer Barutcuoglu et. al 2006]). Kaggle data set is representative of the problem: https://www.kaggle.com/jhoward/nb-svm-strong-linear-baseline/data.

Several other interesting problem in text ana

Машинное обучение

#video

🎥 Лекция 1 | Машинное обучение | Сергей Николенко | Лекториум
👁 2 раз ⏳ 5396 сек.
Лекция 1 | Курс: Машинное обучение | Лектор: Сергей Николенко | Организатор: Математическая лаборатория имени П.Л.Чебышева СПбГУ

Смотрите это виде...

🎥 Лекция 2 | Машинное обучение | Сергей Николенко | Лекториум
👁 1 раз ⏳ 4251 сек.
Лекция 2 | Курс: Машинное обучение | Лектор: Сергей Николенко | Организатор: Математическая лаборатория имени П.Л.Чебышева СПбГУ

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🎥 Лекция 3 | Машинное обучение | Сергей Николенко | Лекториум
👁 1 раз ⏳ 3352 сек.
Лекция 3 | Курс: Машинное обучение | Лектор: Сергей Николенко | Организатор: Математическая лаборатория имени П.Л.Чебышева СПбГУ

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🎥 Лекция 4 | Машинное обучение | Сергей Николенко | Лекториум
👁 1 раз ⏳ 6109 сек.
Лекция 4 | Курс: Машинное обучение | Лектор: Сергей Николенко | Организатор: Математическая лаборатория имени П.Л.Чебышева СПбГУ

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🎥 Лекция 5 | Машинное обучение | Сергей Николенко | Лекториум
👁 1 раз ⏳ 5170 сек.
Лекция 5 | Курс: Машинное обучение | Лектор: Сергей Николенко | Организатор: Математическая лаборатория имени П.Л.Чебышева СПбГУ

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🎥 Лекция 6 | Машинное обучение | Сергей Николенко | Лекториум
👁 1 раз ⏳ 5297 сек.
Лекция 6 | Курс: Машинное обучение | Лектор: Сергей Николенко | Организатор: Математическая лаборатория имени П.Л.Чебышева СПбГУ

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​рименение R для утилитарных задач
#Data Mining

Хороший инструмент + наличие навыков работы с ним, что достигается путем практики, позволяет легко и элегантно решать множество различных «как бы» нетипичных задач. Ниже пара подобных примеров. Уверен, что многие могут этот список расширить.
https://habr.com/ru/post/464849/

🔗 Применение R для утилитарных задач
Хороший инструмент + наличие навыков работы с ним, что достигается путем практики, позволяет легко и элегантно решать множество различных «как бы» нетипичных зад...

​Visualizing Eigenvalues and Eigenvectors

🔗 Visualizing Eigenvalues and Eigenvectors
Eigenvalues and Eigenvectors are a very important concept in Linear Algebra and Machine Learning in general. In my previous article, I’ve…

​15 книг по машинному обучению для начинающих

Сделал подборку книг по Machine Learning для тех, кто хочет разобраться, что да как.
Добавляйте в закладки и делитесь с коллегами!
https://habr.com/ru/post/464871/

🔗 15 книг по машинному обучению для начинающих
Сделал подборку книг по Machine Learning для тех, кто хочет разобраться, что да как. Добавляйте в закладки и делитесь с коллегами! Книги по машинному обучению...

​Eric Weinstein: Struggle Mightily but Give Yourself a Break | AI Podcast Clips

🔗 Eric Weinstein: Struggle Mightily but Give Yourself a Break | AI Podcast Clips
This is a clip from a conversation with Eric Weinstein on the Artificial Intelligence podcast. You can watch the full conversation here: http://bit.ly/2Hp8due If you enjoy these, consider subscribing, sharing, and commenting below. Full episode: http://bit.ly/2Hp8due Full episodes playlist: http://bit.ly/2EcbaKf Clips playlist: http://bit.ly/2JYkbfZ Podcast website: https://lexfridman.com/ai Eric Weinstein is a mathematician, economist, physicist, and managing director of Thiel Capital. He formed the "int