Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!
🔗 Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!
This meetup was recorded in Mountain View, California on January 24th 2019. Slides from the meetup can be viewed here: https://www.slideshare.net/0xdata/get-...
🔗 Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!
This meetup was recorded in Mountain View, California on January 24th 2019. Slides from the meetup can be viewed here: https://www.slideshare.net/0xdata/get-...
YouTube
Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!
This meetup was recorded in Mountain View, California on January 24th 2019. Slides from the meetup can be viewed here: https://www.slideshare.net/0xdata/get-...
s this the BEST BOOK on Machine Learning? Hands On Machine Learning Review
🎥 Is this the BEST BOOK on Machine Learning? Hands On Machine Learning Review
👁 1 раз ⏳ 331 сек.
🎥 Is this the BEST BOOK on Machine Learning? Hands On Machine Learning Review
👁 1 раз ⏳ 331 сек.
Hands On Machine Learning with Scikit Learn and Tensorflow published by O'Reilly and written by Aurelien Geron could just be the best practical book on machine learning. In this review I explain why.
You can buy the book from my Amazon Page ►https://www.amazon.com/shop/pythonprogrammer (affiliate links)
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Programming Learning Resources
Coursera https://www.coursera.org/specializationsVk
Is this the BEST BOOK on Machine Learning? Hands On Machine Learning Review
Hands On Machine Learning with Scikit Learn and Tensorflow published by O'Reilly and written by Aurelien Geron could just be the best practical book on machine learning. In this review I explain why.
You can buy the book from my Amazon Page ►https://ww…
You can buy the book from my Amazon Page ►https://ww…
🎥 Machine Learning With Tensor Flow | Recurrent Neural Networks | Part 3| Eduonix
👁 1 раз ⏳ 980 сек.
👁 1 раз ⏳ 980 сек.
A recurrent neural network (RNN) is a type of artificial neural network commonly used in speech recognition and natural language processing (NLP). RNNs are designed to recognize a data's sequential characteristics and use patterns to predict the next likely scenario. In this video, you will go through the Basics and give the overall explanation of what it is and how it works. Let's learn!!
Want to learn Machine Learning With TensorFlow in Detail? Check out our course Machine Learning With TensorFlow The PrVk
Machine Learning With Tensor Flow | Recurrent Neural Networks | Part 3| Eduonix
A recurrent neural network (RNN) is a type of artificial neural network commonly used in speech recognition and natural language processing (NLP). RNNs are designed to recognize a data's sequential characteristics and use patterns to predict the next likely…
Тест Тьюринга на конференции OpenTalks.AI !
3-й всероссийский конкурс русскоговорящих чат-ботов в формате теста Тьюринга пройдет на конференции OpenTalks.AI! Конкурс организует «Лаборатория Наносемантика» и OpenTalks.AI при поддержке компании МТС, Серебряного партнера конференции!
Компании-победители получат призы:
• 1 место – 200,000 руб.
• 2 место – 150,000 руб.
• 3 место – 100,000 руб.
Каждый желающий может стать экспертом в этом конкурсе, для этого необходимо зарегистрироваться в Телеграм боте @TuringTestRussiaBot и в период с 14 по 16 февраля поговорить в этом чате с несколькими собеседниками и потом угадать, с кем Вы разговаривали – с человеком или ботом. Наиболее активные эксперты, которые угадают точнее всего, получат призы:
• 1 место – 20,000 руб.
• 2 место – 15,000 руб.
• 3 место – 10,000 руб.
Конкурс будет проходить 14-16 февраля, объявление результатов и награждение победителей состоится на конференции 16 февраля. Подробности и регистрация участников - на странице конкурса http://opentalks.ai/ru/turing-test
🔗 OpenTalks.AI - Тест Тьюринга
OpenTalks.AI - Тест Тьюринга
3-й всероссийский конкурс русскоговорящих чат-ботов в формате теста Тьюринга пройдет на конференции OpenTalks.AI! Конкурс организует «Лаборатория Наносемантика» и OpenTalks.AI при поддержке компании МТС, Серебряного партнера конференции!
Компании-победители получат призы:
• 1 место – 200,000 руб.
• 2 место – 150,000 руб.
• 3 место – 100,000 руб.
Каждый желающий может стать экспертом в этом конкурсе, для этого необходимо зарегистрироваться в Телеграм боте @TuringTestRussiaBot и в период с 14 по 16 февраля поговорить в этом чате с несколькими собеседниками и потом угадать, с кем Вы разговаривали – с человеком или ботом. Наиболее активные эксперты, которые угадают точнее всего, получат призы:
• 1 место – 20,000 руб.
• 2 место – 15,000 руб.
• 3 место – 10,000 руб.
Конкурс будет проходить 14-16 февраля, объявление результатов и награждение победителей состоится на конференции 16 февраля. Подробности и регистрация участников - на странице конкурса http://opentalks.ai/ru/turing-test
🔗 OpenTalks.AI - Тест Тьюринга
OpenTalks.AI - Тест Тьюринга
opentalks.ai
OpenTalks.AI - Тест Тьюринга
🎥 MERA - ML meetup - Jan 2019 - Погружение в Machine Learning. Участвуем в Kaggle соревнованиях!
👁 1 раз ⏳ 1862 сек.
👁 1 раз ⏳ 1862 сек.
Выступление Антона Чивкунова на митапе MERA по машинному обучению. Когда ты начинаешь свой путь в области Data Science и Machine Learning, поражает обилие разных материалов для самостоятельного изучения, но без навыков применения все эти знания малого стоят. Где же взять этот опыт применения машинного обучения на реальных «взрослых» задачах? Тут нам на помощь приходит сервис Kaggle со своей облачной средой разработки/выполнения и действительно крутым сообществом Data Science инженеров. На примере участия вVk
MERA - ML meetup - Jan 2019 - Погружение в Machine Learning. Участвуем в Kaggle соревнованиях!
Выступление Антона Чивкунова на митапе MERA по машинному обучению. Когда ты начинаешь свой путь в области Data Science и Machine Learning, поражает обилие разных материалов для самостоятельного изучения, но без навыков применения все эти знания малого стоят.…
I Built My Own Self-Driving Car. Part #3
In the last article, I have introduced you to a very simple lane detection with OpenCV. Taking into account the simplicity, it was doing well. However, it was not up to my expectations. Looks like the current solution that I am going to show you today does not get better unless you want switch to the Recurrent Convolutional Neural Networks (and this is exactly what I am up to). We are going to talk about a way to get better results based on the Hough Transform method output.
#programming #IT #artificialintellegence #developer #HaarCascade #Python #OpenCV #MadDevs
https://blog.maddevs.io/i-built-my-own-self-driving-car-part-3-1ca1d85e9d59
🔗 I Built My Own Self-Driving Car. Part #3 – Mad Devs
In the last article, I have introduced you to a very simple lane detection with OpenCV. Taking into account the simplicity, it was doing well. However, it was not up to my expectations. Looks like the current solution that I am going to show you today does not get better unless you want switch to the Recurrent Convolutional Neural Networks (and this is exactly what I am up to). We are going to talk about a way to get better results based on the Hough Transform method output.
#programming #IT #artificialintellegence #developer #HaarCascade #Python #OpenCV #MadDevs
https://blog.maddevs.io/i-built-my-own-self-driving-car-part-3-1ca1d85e9d59
🔗 I Built My Own Self-Driving Car. Part #3 – Mad Devs
I Built My Own Self-Driving Car. Part #2
In my last article, I have played around with OpenCV and Haar Cascade Classifier in order to detect vehicles. It did not perform very well though. There were many false predictions and the FPS could not get above 15. Today I will introduce you to the third version of the YOLO algorithm developed for the Darknet and ported to Tensorflow and Keras so we can use a nice and shiny Python environment. We are not going to train our own model today and use pre-trained weights.
#programming #IT #artificialintellegence #developer #HaarCascade #Python #OpenCV #MadDevs
https://blog.maddevs.io/i-built-my-own-self-driving-car-part-2-e3894ce4eb42
🔗 I Built My Own Self-Driving Car. Part #2 – Mad Devs
In my last article, I have played around with OpenCV and Haar Cascade Classifier in order to detect vehicles. It did not perform very well though. There were many false predictions and the FPS could not get above 15. Today I will introduce you to the third version of the YOLO algorithm developed for the Darknet and ported to Tensorflow and Keras so we can use a nice and shiny Python environment. We are not going to train our own model today and use pre-trained weights.
#programming #IT #artificialintellegence #developer #HaarCascade #Python #OpenCV #MadDevs
https://blog.maddevs.io/i-built-my-own-self-driving-car-part-2-e3894ce4eb42
🔗 I Built My Own Self-Driving Car. Part #2 – Mad Devs
New interesting research from Facebook about simulating focus effect with DNN
https://research.fb.com/publications/deepfocus-siggraph-asia-2018/
🔗 DeepFocus: Learned Image Synthesis for Computational Displays
In this paper, we introduce DeepFocus, a generic, end-to-end convolutional neural network designed to efficiently solve the full range of computational tasks for accommodation-supporting HMDs. This network is demonstrated to accurately synthesize defocus blur, focal stacks, multilayer decompositions, and multiview imagery using only commonly available RGB-D images, enabling real-time, near-correct depictions of retinal blur with a broad set of accommodation-supporting HMDs.
https://research.fb.com/publications/deepfocus-siggraph-asia-2018/
🔗 DeepFocus: Learned Image Synthesis for Computational Displays
In this paper, we introduce DeepFocus, a generic, end-to-end convolutional neural network designed to efficiently solve the full range of computational tasks for accommodation-supporting HMDs. This network is demonstrated to accurately synthesize defocus blur, focal stacks, multilayer decompositions, and multiview imagery using only commonly available RGB-D images, enabling real-time, near-correct depictions of retinal blur with a broad set of accommodation-supporting HMDs.
Facebook Research
DeepFocus: Learned Image Synthesis for Computational Displays - Facebook Research
In this paper, we introduce DeepFocus, a generic, end-to-end convolutional neural network designed to efficiently solve the full range of computational tasks for accommodation-supporting HMDs. This network is demonstrated to accurately synthesize defocus…
Applied Deep Learning with PyTorch - Full Course
🎥 Applied Deep Learning with PyTorch - Full Course
👁 1 раз ⏳ 20404 сек.
🎥 Applied Deep Learning with PyTorch - Full Course
👁 1 раз ⏳ 20404 сек.
In this course you will learn the key concepts behind deep learning and how to apply the concepts to a real-life project using PyTorch and Python.
You'll learn the following:
⌨️ RNNs and LSTMs
⌨️ Sequence Modeling
⌨️ PyTorch
⌨️ Building a Chatbot in PyTorch
⭐️Requirements ⭐️
⌨️ Some Basic High School Mathematics
⌨️ Some Basic Programming Knowledge
⌨️ Some basic Knowledge about Neural Networks
⭐️Contents ⭐️
⌨️ (0:00:08) Recurrent Nerual Networks - RNNs and LSTMs
⌨️ (0:35:54) Sequence-To-Sequence Models
⌨️Vk
Applied Deep Learning with PyTorch - Full Course
In this course you will learn the key concepts behind deep learning and how to apply the concepts to a real-life project using PyTorch and Python.
You'll learn the following:
⌨️ RNNs and LSTMs
⌨️ Sequence Modeling
⌨️ PyTorch
⌨️ Building a Chatbot in PyTorch…
You'll learn the following:
⌨️ RNNs and LSTMs
⌨️ Sequence Modeling
⌨️ PyTorch
⌨️ Building a Chatbot in PyTorch…
Hands-On with Unsupervised Learning
A quick tutorial on k-means clustering and principal component analysis (PCA).
🔗 Hands-On with Unsupervised Learning – Towards Data Science
A quick tutorial on k-means clustering and principal component analysis (PCA).
A quick tutorial on k-means clustering and principal component analysis (PCA).
🔗 Hands-On with Unsupervised Learning – Towards Data Science
A quick tutorial on k-means clustering and principal component analysis (PCA).
Towards Data Science
Hands-On with Unsupervised Learning
A quick tutorial on k-means clustering and principal component analysis (PCA).
Building an Experimentation Framework for Composite Algorithms
🔗 Building an Experimentation Framework for Composite Algorithms
Its often very useful to develop a framework quickly on top of an existing ML Library for changing the model hyper-parameters and blending…
🔗 Building an Experimentation Framework for Composite Algorithms
Its often very useful to develop a framework quickly on top of an existing ML Library for changing the model hyper-parameters and blending…
Towards Data Science
Building an Experimentation Framework for Composite Algorithms
Its often very useful to develop a framework quickly on top of an existing ML Library for changing the model hyper-parameters and blending…
Modernizing Life Science Manufacturing with AWS Machine Learning
🔗 Modernizing Life Science Manufacturing with AWS Machine Learning
Learn more about Pharma & Biotech in the Cloud - https://amzn.to/2CWCmhc In this webinar, you will hear from the pharmaceutical manufacturer Novo Nordisk, an...
🔗 Modernizing Life Science Manufacturing with AWS Machine Learning
Learn more about Pharma & Biotech in the Cloud - https://amzn.to/2CWCmhc In this webinar, you will hear from the pharmaceutical manufacturer Novo Nordisk, an...
YouTube
Modernizing Life Science Manufacturing with AWS Machine Learning
Learn more about Pharma & Biotech in the Cloud - https://amzn.to/2CWCmhc In this webinar, you will hear from the pharmaceutical manufacturer Novo Nordisk, an...
Margaret Maynard-Reid: Machine Learning for Mobile with TensorFlow
🎥 Margaret Maynard-Reid: Machine Learning for Mobile with TensorFlow
👁 1 раз ⏳ 3547 сек.
🎥 Margaret Maynard-Reid: Machine Learning for Mobile with TensorFlow
👁 1 раз ⏳ 3547 сек.
Recorded at GDG Boulder on 2019-01-29:
https://www.meetup.com/Google-Developer-Group-Boulder/events/257013855/
Are you interested in getting started with machine learning, and making intelligent apps with the most popular deep learning framework TensorFlow? Come to this talk to learn your various options: from using ready made APIs to training your own custom models. You will learn the end to end process of how to train a model with TensorFlow high level API tf.Keras, convert to a TensorFlow Lite model andVk
Margaret Maynard-Reid: Machine Learning for Mobile with TensorFlow
Recorded at GDG Boulder on 2019-01-29:
https://www.meetup.com/Google-Developer-Group-Boulder/events/257013855/
Are you interested in getting started with machine learning, and making intelligent apps with the most popular deep learning framework TensorFlow?…
https://www.meetup.com/Google-Developer-Group-Boulder/events/257013855/
Are you interested in getting started with machine learning, and making intelligent apps with the most popular deep learning framework TensorFlow?…
Премия имени Ильи Сегаловича. Рассказ о компьютерных науках и публикациях по случаю запуска
🔗 Премия имени Ильи Сегаловича. Рассказ о компьютерных науках и публикациях по случаю запуска
Сегодня мы запускаем научную премию имени Ильи Сегаловича iseg. Она будет присуждаться за достижения в области компьютерных наук. Студенты и аспиранты могут...
🔗 Премия имени Ильи Сегаловича. Рассказ о компьютерных науках и публикациях по случаю запуска
Сегодня мы запускаем научную премию имени Ильи Сегаловича iseg. Она будет присуждаться за достижения в области компьютерных наук. Студенты и аспиранты могут...
Хабр
Премия имени Ильи Сегаловича. Рассказ о компьютерных науках и публикациях по случаю запуска
Сегодня мы запускаем научную премию имени Ильи Сегаловича iseg. Она будет присуждаться за достижения в области компьютерных наук. Студенты и аспиранты могут по...
Configurable Keras Multilayer Perceptron Neural Network - Part 1: Configuration
https://www.youtube.com/watch?v=icVMkykh_qE
🎥 Configurable Keras Multilayer Perceptron Neural Network - Part 1: Configuration
👁 1 раз ⏳ 4554 сек.
https://www.youtube.com/watch?v=icVMkykh_qE
🎥 Configurable Keras Multilayer Perceptron Neural Network - Part 1: Configuration
👁 1 раз ⏳ 4554 сек.
First video of 2019. It was a rather terrible one. Kept coughing and having some technical difficulties with python. Disclaimer: Not a python programmer so there will be a lot of bumps along the way.
This video is the first part of a series of videos to implement a feed forward multi-layer perceptron network using keras and python. The difference between this and other videos on the Internet is that we want to build an application (command line application) and not just another set of function calls to buiYouTube
Configurable Keras Multilayer Perceptron Neural Network - Part 1: Configuration
First video of 2019. It was a rather terrible one. Kept coughing and having some technical difficulties with python. Disclaimer: Not a python programmer so there will be a lot of bumps along the way.
This video is the first part of a series of videos to…
This video is the first part of a series of videos to…
🎥 ЛУЧШИЙ COMBO VINE 2019 ТРЕКИ В ОПИСАНИИ
👁 1 раз ⏳ 638 сек.
👁 1 раз ⏳ 638 сек.
Решил сегодня сделать топовую Combo Vine, и вот что получилось, приятного просмотра, поддержите лайком, и не забудьте подписаться на канал.
Треки:
1. -----
2. Xk4001 - l watch the purpl
3. Vi Veri - Veniversum Vivus Vici
4. #268 Iceman Bells X Auto Combo
5. OG RON - Act A Fool
6. Cono Puri
7. #855 MOLDAVITE X MXNT - EXODUS X Auto Combo
8. -----
9. #961 Mesqo - Spotlight (Bass Version) X Auto Combo
10. Sagath, Fatal-M - Мистерия
11. Auto Combo - #SIRI
12. ------
13. plug - akihoma
14. Bad Decisions - YeahVk
ЛУЧШИЙ COMBO VINE 2019 ТРЕКИ В ОПИСАНИИ
Решил сегодня сделать топовую Combo Vine, и вот что получилось, приятного просмотра, поддержите лайком, и не забудьте подписаться на канал.
Треки:
1. -----
2. Xk4001 - l watch the purpl
3. Vi Veri - Veniversum Vivus Vici
4. #268 Iceman Bells X Auto Combo…
Треки:
1. -----
2. Xk4001 - l watch the purpl
3. Vi Veri - Veniversum Vivus Vici
4. #268 Iceman Bells X Auto Combo…
Книга "Python Data Science Handbook" - это подробное руководство по самым разным вычислительным и статистическим методам, без которых немыслима любая интенсивная обработка данных, научные исследования и передовые разработки. Читатели, уже имеющие опыт программирования и желающие эффективно использовать Python в сфере Data Science, найдут в этой книге ответы на всевозможные вопросы, например: 1) как мне считать этот формат данных в мой скрипт? 2) Как преобразовать, очистить эти данные и манипулировать ими? 3) Как визуализировать данные такого типа? Как при помощи этих данных разобраться в ситуации, получить ответы на вопросы, построить статистические модели или реализовать машинное обучение?
📝 Плас Дж. Вандер - Python для сложных задач наука о данных и машинное обучение (Бестселлеры O'Reilly) - 2018.PDF - 💾12 530 081
📝 Плас Дж. Вандер - Python для сложных задач наука о данных и машинное обучение (Бестселлеры O'Reilly) - 2018.PDF - 💾12 530 081
