🎥 Chaos and Pain in Machine Learning and the DevOps for ML Manifesto - Luke Marsden | ODSC Europe 2019
👁 1 раз ⏳ 2433 сек.
👁 1 раз ⏳ 2433 сек.
Luke Marsden, CEO and founder of Dotscience, is an industry veteran and an expert in DevOps and container storage. He founded Dotscience on the belief that operationalizing Machine Learning should be just as easy, fast and safe as modern software engineering became when DevOps revolutionized the industry.
Luke Marsden was speaking at ODSC Europe 2019.
→ To watch more videos like this, visit https://learnai.odsc.com/ ←
Most AI/ML projects start shipping models into production, where they can deliver businVk
Chaos and Pain in Machine Learning and the DevOps for ML Manifesto - Luke Marsden | ODSC Europe 2019
Luke Marsden, CEO and founder of Dotscience, is an industry veteran and an expert in DevOps and container storage. He founded Dotscience on the belief that operationalizing Machine Learning should be just as easy, fast and safe as modern software engineering…
Advancing Self-Supervised and Semi-Supervised Learning with SimCLR">
Advancing Self-Supervised and Semi-Supervised Learning with SimCLR
🔗 Advancing Self-Supervised and Semi-Supervised Learning with SimCLR
Posted by Ting Chen, Research Scientist, and Geoffrey Hinton, VP & Engineering Fellow, Google Research Recently, natural language proces...
Advancing Self-Supervised and Semi-Supervised Learning with SimCLR
🔗 Advancing Self-Supervised and Semi-Supervised Learning with SimCLR
Posted by Ting Chen, Research Scientist, and Geoffrey Hinton, VP & Engineering Fellow, Google Research Recently, natural language proces...
Googleblog
Advancing Self-Supervised and Semi-Supervised Learning with SimCLR
Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contras
🔗 Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contras
Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contrast, Programmer Sought, the best programmer technical posts sharing site.
🔗 Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contras
Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contrast, Programmer Sought, the best programmer technical posts sharing site.
Programmersought
Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contrast - Programmer Sought
Common deep learning framework Theano, TensorFlow, Keras, Caffe/Caffe2, MXNet, CNTK, PyTorch contrast, Programmer Sought, the best programmer technical posts sharing site.
Цифровизация оборота лекарственных препаратов на примере кейса для сети аптек «Планета здоровья»
🔗 Цифровизация оборота лекарственных препаратов в эпоху коронавируса. Кейс для сети аптек «Планета здоровья»
3 апреля 2020 года Президент РФ подписал закон, позволяющий аптекам продавать безрецептурные препараты через интернет. Этот закон был вынесен на рассмотрение ещё...
🔗 Цифровизация оборота лекарственных препаратов в эпоху коронавируса. Кейс для сети аптек «Планета здоровья»
3 апреля 2020 года Президент РФ подписал закон, позволяющий аптекам продавать безрецептурные препараты через интернет. Этот закон был вынесен на рассмотрение ещё...
Хабр
Цифровизация оборота лекарственных препаратов на примере кейса для сети аптек «Планета здоровья»
3 апреля 2020 года Президент РФ подписал закон, позволяющий аптекам продавать безрецептурные препараты через интернет. Этот закон был вынесен на рассмотрение ещё в конце 2017 года. C того времени...
Подбор важности фич для k-nearest neighbors (ну или других гиперпараметров) спуском похожим на градиентный
🔗 Подбор важности фич для k-nearest neighbors (ну или других гиперпараметров) спуском похожим на градиентный
Экспериментируя с простейшей задачкой машинного обучения я обнаружил, что интересно было бы подобрать в довольно широком диапазоне значения 18 гиперпараметров о...
🔗 Подбор важности фич для k-nearest neighbors (ну или других гиперпараметров) спуском похожим на градиентный
Экспериментируя с простейшей задачкой машинного обучения я обнаружил, что интересно было бы подобрать в довольно широком диапазоне значения 18 гиперпараметров о...
Хабр
Подбор важности фич для k-nearest neighbors (ну или других гиперпараметров) спуском похожим на градиентный
Экспериментируя с простейшей задачкой машинного обучения я обнаружил, что интересно было бы подобрать в довольно широком диапазоне значения 18 гиперпараметров одновременно. В моём случае всё было на...
5 шагов к созданию качественных визуализаций с matplotlib.
https://proglib.io/w/56629933
🔗 5 Steps to Amazing Visualizations with Matplotlib
Matplotlib sucks. By default. Here’s what to do about it.
https://proglib.io/w/56629933
🔗 5 Steps to Amazing Visualizations with Matplotlib
Matplotlib sucks. By default. Here’s what to do about it.
Medium
5 Steps to Amazing Visualizations with Matplotlib
Matplotlib sucks. By default. Here’s what to do about it.
Extracting headers and paragraphs from pdf using PyMuPDF
🔗 Extracting headers and paragraphs from pdf using PyMuPDF
A naive route to parsing headers and paragraphs from pdf documents
🔗 Extracting headers and paragraphs from pdf using PyMuPDF
A naive route to parsing headers and paragraphs from pdf documents
Medium
Extracting headers and paragraphs from pdf using PyMuPDF
A naive route to parsing headers and paragraphs from pdf documents
🎥 A. David Redish: "Cross-species translation through computational analyses - implications for un..."
👁 1 раз ⏳ 3298 сек.
👁 1 раз ⏳ 3298 сек.
Deep Learning and Medical Applications 2020
"Cross-species translation through computational analyses - implications for understanding and modifying psychiatric treatments"
A. David Redish - University of Minnesota, Twin Cities
Abstract: In the new conceptual framework of computational psychiatry, psychiatric dysfunctions are seen as problems in information processing of environmental situations. This new framework has three implications which I will explore in this talk. (1) Diagnosis should align to infVk
A. David Redish: "Cross-species translation through computational analyses - implications for un..."
Deep Learning and Medical Applications 2020
"Cross-species translation through computational analyses - implications for understanding and modifying psychiatric treatments"
A. David Redish - University of Minnesota, Twin Cities
Abstract: In the new conceptual…
"Cross-species translation through computational analyses - implications for understanding and modifying psychiatric treatments"
A. David Redish - University of Minnesota, Twin Cities
Abstract: In the new conceptual…
🎥 3. Class 3 : Building First Deep Neural Network #DeepLearning2020
👁 1 раз ⏳ 1770 сек.
👁 1 раз ⏳ 1770 сек.
Hello Everyone,
This is class 3 of Deeplearning 2020 - Free hands-on course on Deep Learning.
For questions/queries : please post in comments section
Reach the instructor at : instructor@manifoldailearning.in
Corporate Enquiries : support@manifoldailearning.in
Special Bootcamp on Data Science DeepLearning reach us : support@manifoldailearning.inVk
3. Class 3 : Building First Deep Neural Network #DeepLearning2020
Hello Everyone,
This is class 3 of Deeplearning 2020 - Free hands-on course on Deep Learning.
For questions/queries : please post in comments section
Reach the instructor at : instructor@manifoldailearning.in
Corporate Enquiries : support@manifoldailearning.in…
This is class 3 of Deeplearning 2020 - Free hands-on course on Deep Learning.
For questions/queries : please post in comments section
Reach the instructor at : instructor@manifoldailearning.in
Corporate Enquiries : support@manifoldailearning.in…
🎥 Machine Learning Interview Questions | Machine Learning Interview Preparation | Intellipaat
👁 1 раз ⏳ 2729 сек.
👁 1 раз ⏳ 2729 сек.
This machine learning interview questions and answers video is an exclusive machine learning interview preparation tutorial where you will learn everything about machine learning latest interview questions with detailed answer asked in top MNCs recently. If you are preparing for machine learning job then this is a must watch video for you. We have covered machine learning basic questions to advance questions so that this video caters to everyone at any stage of learning machine learning.
🔥🔥Intellipaat MacVk
Machine Learning Interview Questions | Machine Learning Interview Preparation | Intellipaat
This machine learning interview questions and answers video is an exclusive machine learning interview preparation tutorial where you will learn everything about machine learning latest interview questions with detailed answer asked in top MNCs recently.…
ML Code Completeness Checklist
https://medium.com/paperswithcode/ml-code-completeness-checklist-e9127b168501
Tips for Publishing Research Code: https://github.com/paperswithcode/releasing-research-code
Facebook blog: https://ai.facebook.com/blog/new-code-completeness-checklist-and-reproducibility-updates/
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🔗 ML Code Completeness Checklist
Collated best practices from most popular ML research repositories — used for code submissions at NeurIPS 2020.
https://medium.com/paperswithcode/ml-code-completeness-checklist-e9127b168501
Tips for Publishing Research Code: https://github.com/paperswithcode/releasing-research-code
Facebook blog: https://ai.facebook.com/blog/new-code-completeness-checklist-and-reproducibility-updates/
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🔗 ML Code Completeness Checklist
Collated best practices from most popular ML research repositories — used for code submissions at NeurIPS 2020.
Medium
ML Code Completeness Checklist
Collated best practices from most popular ML research repositories — used for code submissions at NeurIPS 2020.
New code completeness checklist and reproducibility updates
🔗 New code completeness checklist and reproducibility updates
Today, @paperswithcode introduced its new ML Code Completeness Checklist, building on the AI reproducibility work from FAIR Managing Director Joelle Pineau
🔗 New code completeness checklist and reproducibility updates
Today, @paperswithcode introduced its new ML Code Completeness Checklist, building on the AI reproducibility work from FAIR Managing Director Joelle Pineau
Facebook
New code completeness checklist and reproducibility updates
Today, @paperswithcode introduced its new ML Code Completeness Checklist, building on the AI reproducibility work from FAIR Managing Director Joelle Pineau
How Airbus Detects Anomalies in ISS Telemetry Data Using TFX
🔗 How Airbus Detects Anomalies in ISS Telemetry Data Using TFX
🔗 How Airbus Detects Anomalies in ISS Telemetry Data Using TFX
blog.tensorflow.org
How Airbus Detects Anomalies in ISS Telemetry Data Using TFX
The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.
Попытка использовать ИИ в детекторе лжи лишь усугубляет проблему распознавания обмана
🔗 Попытка использовать ИИ в детекторе лжи лишь усугубляет проблему распознавания обмана
Подробнейшее исследование попыток использования искусственного интеллекта в распознавании лжи До того, как полиграф вынес ему вердикт «виновен», Эммануэль Мерв...
🔗 Попытка использовать ИИ в детекторе лжи лишь усугубляет проблему распознавания обмана
Подробнейшее исследование попыток использования искусственного интеллекта в распознавании лжи До того, как полиграф вынес ему вердикт «виновен», Эммануэль Мерв...
Хабр
Попытка использовать ИИ в детекторе лжи лишь усугубляет проблему распознавания обмана
Подробнейшее исследование попыток использования искусственного интеллекта в распознавании лжи До того, как полиграф вынес ему вердикт «виновен», Эммануэль Мервилус работал в компании, производящей...
RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.
RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of its internals are framework agnostic.
The Ray Team : https://ray.readthedocs.io/en/latest/rllib.html
🔗 RLlib: Scalable Reinforcement Learning — Ray 0.9.0.dev0 documentation
RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of its internals are framework agnostic.
The Ray Team : https://ray.readthedocs.io/en/latest/rllib.html
🔗 RLlib: Scalable Reinforcement Learning — Ray 0.9.0.dev0 documentation
Как мы считаем людей с помощью компьютерного зрения
🔗 Как мы считаем людей с помощью компьютерного зрения
Фото из открытых источников Массовые скопления людей создают проблемы в самых разных областях (ритейл, госслужбы, банки, застройщики). Заказчикам необходимо об...
🔗 Как мы считаем людей с помощью компьютерного зрения
Фото из открытых источников Массовые скопления людей создают проблемы в самых разных областях (ритейл, госслужбы, банки, застройщики). Заказчикам необходимо об...
Хабр
Как мы считаем людей с помощью компьютерного зрения
Фото из открытых источников Массовые скопления людей создают проблемы в самых разных областях (ритейл, госслужбы, банки, застройщики). Заказчикам необходимо объединять и мониторить информацию о...
uDepth: Real-time 3D Depth Sensing on the Pixel 4">
uDepth: Real-time 3D Depth Sensing on the Pixel 4
🔗 uDepth: Real-time 3D Depth Sensing on the Pixel 4
Posted by Michael Schoenberg, uDepth Software Lead and Adarsh Kowdle, uDepth Hardware/Systems Lead, Google Research The ability to deter...
uDepth: Real-time 3D Depth Sensing on the Pixel 4
🔗 uDepth: Real-time 3D Depth Sensing on the Pixel 4
Posted by Michael Schoenberg, uDepth Software Lead and Adarsh Kowdle, uDepth Hardware/Systems Lead, Google Research The ability to deter...
Googleblog
uDepth: Real-time 3D Depth Sensing on the Pixel 4
🎥 Knowledge - Lecture 1 - CS50's Introduction to Artificial Intelligence with Python
👁 1 раз ⏳ 6464 сек.
👁 1 раз ⏳ 6464 сек.
00:00:00 - Introduction
00:00:15 - Knowledge
00:04:52 - Propositional Logic
00:21:47 - Inference
00:40:06 - Knowledge Engineering
01:04:33 - Inference Rules
01:30:31 - Resolution
01:38:25 - First-Order LogicVk
Knowledge - Lecture 1 - CS50's Introduction to Artificial Intelligence with Python
00:00:00 - Introduction
00:00:15 - Knowledge
00:04:52 - Propositional Logic
00:21:47 - Inference
00:40:06 - Knowledge Engineering
01:04:33 - Inference Rules
01:30:31 - Resolution
01:38:25 - First-Order Logic
00:00:15 - Knowledge
00:04:52 - Propositional Logic
00:21:47 - Inference
00:40:06 - Knowledge Engineering
01:04:33 - Inference Rules
01:30:31 - Resolution
01:38:25 - First-Order Logic
🎥 Neural Networks - Lecture 5 - CS50's Introduction to Artificial Intelligence with Python
👁 1 раз ⏳ 6080 сек.
👁 1 раз ⏳ 6080 сек.
00:00:00 - Introduction
00:00:15 - Neural Networks
00:05:41 - Activation Functions
00:07:47 - Neural Network Structure
00:16:02 - Gradient Descent
00:30:00 - Multilayer Neural Networks
00:32:58 - Backpropagation
00:36:27 - Overfitting
00:38:52 - TensorFlow
00:53:01 - Computer Vision
00:58:09 - Image Convolution
01:08:18 - Convolutional Neural Networks
01:27:03 - Recurrent Neural NetworksVk
Neural Networks - Lecture 5 - CS50's Introduction to Artificial Intelligence with Python
00:00:00 - Introduction
00:00:15 - Neural Networks
00:05:41 - Activation Functions
00:07:47 - Neural Network Structure
00:16:02 - Gradient Descent
00:30:00 - Multilayer Neural Networks
00:32:58 - Backpropagation
00:36:27 - Overfitting
00:38:52 - TensorFlow…
00:00:15 - Neural Networks
00:05:41 - Activation Functions
00:07:47 - Neural Network Structure
00:16:02 - Gradient Descent
00:30:00 - Multilayer Neural Networks
00:32:58 - Backpropagation
00:36:27 - Overfitting
00:38:52 - TensorFlow…
How we launched a data product in 60 days with AWS
🔗 How we launched a data product in 60 days with AWS
Team of two planned and shipped a beta for 200 users in less than 2 months without quitting their full-time jobs.
🔗 How we launched a data product in 60 days with AWS
Team of two planned and shipped a beta for 200 users in less than 2 months without quitting their full-time jobs.
Medium
How we launched a data product in 60 days with AWS
Team of two planned and shipped a beta for 200 users in less than 2 months without quitting their full-time jobs.