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Подробности у меня на стене!!!
Подробности у меня на стене!!!
🎥 CatBoost - градиентный бустинг от Яндекса
👁 161 раз ⏳ 4853 сек.
👁 161 раз ⏳ 4853 сек.
Приглашённая лекция в рамках курса «Машинное обучение, часть 2» (весна 2018).
Лектор — Анна Вероника Дорогуш (Яндекс).
Страница лекции на сайте CS центра: https://goo.gl/YwePW1Vk
CatBoost - градиентный бустинг от Яндекса
Приглашённая лекция в рамках курса «Машинное обучение, часть 2» (весна 2018).
Лектор — Анна Вероника Дорогуш (Яндекс).
Страница лекции на сайте CS центра: https://goo.gl/YwePW1
Лектор — Анна Вероника Дорогуш (Яндекс).
Страница лекции на сайте CS центра: https://goo.gl/YwePW1
Learn Python - Python Tutorials - DataFlair
🔗 Learn Python - Python Tutorials - DataFlair
Install Python on your machine now and get started with Python today.
🔗 Learn Python - Python Tutorials - DataFlair
Install Python on your machine now and get started with Python today.
DataFlair
Python Tutorials for Beginners – Learn Python Programming - DataFlair
Python Tutorial for Beginners - Learn Python with 370+ Python tutorials, real-time practicals, live projects, quizzes and free courses.
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
https://www.youtube.com/watch?v=s4Lcf9du9L8
🎥 TensorFlow Installation | Step By Step Guide to Install TensorFlow on Windows | Edureka
👁 1 раз ⏳ 546 сек.
https://www.youtube.com/watch?v=s4Lcf9du9L8
🎥 TensorFlow Installation | Step By Step Guide to Install TensorFlow on Windows | Edureka
👁 1 раз ⏳ 546 сек.
*** AI and Deep-Learning with TensorFlow - https://www.edureka.co/ai-deep-learning-with-tensorflow ***
This video provides a step by step installation process of tensorflow. It also provide you with a brief on tensorflow and how different industries are using tensorflow to solve real-life problems.
1:03 What is TensorFlow?
1:43 Applications of TensorFlow
2:51 Installation
------------------------------------------------
*** Machine Learning Podcast - https://castbox.fm/channel/id1832236 ***
Instagram:Ensemble methods: bagging, boosting and stacking
🔗 Ensemble methods: bagging, boosting and stacking
Understanding the key concepts of ensemble learning.
🔗 Ensemble methods: bagging, boosting and stacking
Understanding the key concepts of ensemble learning.
Towards Data Science
Ensemble methods: bagging, boosting and stacking
Understanding the key concepts of ensemble learning.
Remaining Life Estimation with Keras
🔗 Remaining Life Estimation with Keras
From Time Series to Images… Asking to a CNN ‘when does the next fault occour?’
🔗 Remaining Life Estimation with Keras
From Time Series to Images… Asking to a CNN ‘when does the next fault occour?’
Towards Data Science
Remaining Life Estimation with Keras
From Time Series to Images… Asking to a CNN ‘when does the next fault occour?’
🎥 NVIDIA's AI Creates Beautiful Images From Your Sketches
👁 1 раз ⏳ 250 сек.
👁 1 раз ⏳ 250 сек.
If you wish to support the series, please buy anything through this Amazon link - you don't lose anything and we get a small kickback. Thank you so much!
US: https://amzn.to/2FQHPcs
EU: https://amzn.to/2UnB2yF
📝 The paper "Semantic Image Synthesis with Spatially-Adaptive Normalization" and its source code is available here:
https://nvlabs.github.io/SPADE/
https://github.com/NVlabs/SPADE
❤️ Pick up cool perks on our Patreon page: https://www.patreon.com/TwoMinutePapers
🙏 We would like to thank our generouVk
NVIDIA's AI Creates Beautiful Images From Your Sketches
If you wish to support the series, please buy anything through this Amazon link - you don't lose anything and we get a small kickback. Thank you so much!
US: https://amzn.to/2FQHPcs
EU: https://amzn.to/2UnB2yF
📝 The paper "Semantic Image Synthesis with Spatially…
US: https://amzn.to/2FQHPcs
EU: https://amzn.to/2UnB2yF
📝 The paper "Semantic Image Synthesis with Spatially…
10 Python Pandas tricks to make data analysis more enjoyable
🔗 10 Python Pandas tricks to make data analysis more enjoyable
If one has not yet fallen in love with Pandas, it may be because he/she has not seen enough cool examples
🔗 10 Python Pandas tricks to make data analysis more enjoyable
If one has not yet fallen in love with Pandas, it may be because he/she has not seen enough cool examples
Towards Data Science
10 Python Pandas tricks to make data analysis more enjoyable
If one has not yet fallen in love with Pandas, it may be because he/she has not seen enough cool examples
🎥 Extract data using API (Python) - Part 2 | Machine & Deep Learning
👁 1 раз ⏳ 1473 сек.
👁 1 раз ⏳ 1473 сек.
Extract data using API (Python) - Part 2 | Machine & Deep Learning Bootcamp
Welcome to "The AI University".
Subtitles available in: Hindi, English, French
About this video:
This video explains how to extract data from the CoinMarketCap API endpoint using API key provided by CoinMarketCap.This is the continuation and part 2 of previous video where I gave the introduction of APIs. Once extracted data will be stored in pretty as well as text file.
Follow me on Twitter: https://twitter.com/theaiuniversVk
Extract data using API (Python) - Part 2 | Machine & Deep Learning
Extract data using API (Python) - Part 2 | Machine & Deep Learning Bootcamp
Welcome to "The AI University".
Subtitles available in: Hindi, English, French
About this video:
This video explains how to extract data from the CoinMarketCap API endpoint using…
Welcome to "The AI University".
Subtitles available in: Hindi, English, French
About this video:
This video explains how to extract data from the CoinMarketCap API endpoint using…
🎥 Lesson 4. Optimization basics: derivative and gradient
👁 1 раз ⏳ 2613 сек.
👁 1 раз ⏳ 2613 сек.
The "learning" process of the modern AI stands for optimization the loss function given the data, i.e. the features of the objects and the answers (in the Supervised learning setting).
In this lesson the core concepts of optimization methods are considered: derivative and gradient. Thank to them we can use gradient descent to optimize the linera models and one neuron.
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?id=1zxLACGTyzWigd_JkCN76D8GCxyM6LWCf
---
About Deep Learning SVk
Lesson 4. Optimization basics: derivative and gradient
The "learning" process of the modern AI stands for optimization the loss function given the data, i.e. the features of the objects and the answers (in the Supervised learning setting).
In this lesson the core concepts of optimization methods are considered:…
In this lesson the core concepts of optimization methods are considered:…
ahmedfgad/GARI
🔗 ahmedfgad/GARI
This work introduces a simple project called GARI (Genetic Algorithm for Reproducing Images). GARI reproduces a single image using Genetic Algorithm (GA) by evolving pixel values. - ahmedfgad/GARI
🔗 ahmedfgad/GARI
This work introduces a simple project called GARI (Genetic Algorithm for Reproducing Images). GARI reproduces a single image using Genetic Algorithm (GA) by evolving pixel values. - ahmedfgad/GARI
GitHub
GitHub - ahmedfgad/GARI: GARI (Genetic Algorithm for Reproducing Images) reproduces a single image using Genetic Algorithm (GA)…
GARI (Genetic Algorithm for Reproducing Images) reproduces a single image using Genetic Algorithm (GA) by evolving pixel values. - ahmedfgad/GARI
🎥 Lesson 4. Linear models and Gradient Descent
👁 1 раз ⏳ 1942 сек.
👁 1 раз ⏳ 1942 сек.
Linear models are the base algorithms in machine learning, they are used almost everywhere in production. The are the key for understanding the work of one neuron in neural nets.
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?id=1zxLACGTyzWigd_JkCN76D8GCxyM6LWCf
---
About Deep Learning School at PSAMI MIPT
Official website: https://www.dlschool.org
Github-repo: https://github.com/DLSchool/dlschool_english
About PSAMI MIPT
Official website: https://mipt.ru/english/edu/phyVk
Lesson 4. Linear models and Gradient Descent
Linear models are the base algorithms in machine learning, they are used almost everywhere in production. The are the key for understanding the work of one neuron in neural nets.
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?…
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?…
🎥 Tesla Autonomy 3/6: Neural Networks
👁 1 раз ⏳ 2030 сек.
👁 1 раз ⏳ 2030 сек.
Andrej Karpathy, Tesla's deep learning and computer vision expert talks about neural networks.Vk
Tesla Autonomy 3/6: Neural Networks
Andrej Karpathy, Tesla's deep learning and computer vision expert talks about neural networks.
What is Natural Language Processing (NLP)? A bitesize explanation
🔗 What is Natural Language Processing (NLP)? A bitesize explanation
NLP keeps being bounded about as a magic panacea or a digital tower of babel and with many conflicting ideas. I present a quick…
🔗 What is Natural Language Processing (NLP)? A bitesize explanation
NLP keeps being bounded about as a magic panacea or a digital tower of babel and with many conflicting ideas. I present a quick…
Towards Data Science
What is Natural Language Processing (NLP)? A bitesize explanation
NLP keeps being bounded about as a magic panacea or a digital tower of babel and with many conflicting ideas. I present a quick…
🎥 Theoretical Deep Learning. The Information Bottleneck method. Part 1
👁 1 раз ⏳ 5831 сек.
👁 1 раз ⏳ 5831 сек.
In this class we introduce the information bottleneck method. We also discuss what we can learn about the training process of neural nets using this technique.
Find out more: https://github.com/deepmipt/tdl
Our open-source framework to develop and deploy conversational assistants: https://deeppavlov.ai/Vk
Theoretical Deep Learning. The Information Bottleneck method. Part 1
In this class we introduce the information bottleneck method. We also discuss what we can learn about the training process of neural nets using this technique.
Find out more: https://github.com/deepmipt/tdl
Our open-source framework to develop and deploy…
Find out more: https://github.com/deepmipt/tdl
Our open-source framework to develop and deploy…
Разработка поисковой системы на основе векторных представлений слов
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🎥 Разработка поисковой системы на основе векторных представлений слов
👁 1 раз ⏳ 3315 сек.
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🎥 Разработка поисковой системы на основе векторных представлений слов
👁 1 раз ⏳ 3315 сек.
Основой поисковых систем, существующих на данный момент, является инвертированный индекс, с помощью которого происходит выборка документов для ранжирования. Данный подход имеет ряд недостатков. Например, документы, не имеющие пересечения с запросом, но содержащие похожие (синонимичные) слова, никогда не будут попадать в поисковую выдачу.
На этом семинаре будет показан возможный принципиально другой подход к организации поискового индекса с использованием векторных представлений слов, который мы реализуем вVk
Разработка поисковой системы на основе векторных представлений слов
Основой поисковых систем, существующих на данный момент, является инвертированный индекс, с помощью которого происходит выборка документов для ранжирования. Данный подход имеет ряд недостатков. Например, документы, не имеющие пересечения с запросом, но содержащие…
Mind the Machines: a podcast about data science jobs and the future of AI
🔗 Mind the Machines: a podcast about data science jobs and the future of AI
We’ve learned a lot about the data science job market since we launched SharpestMinds. We’ve interviewed thousands of aspiring data…
🔗 Mind the Machines: a podcast about data science jobs and the future of AI
We’ve learned a lot about the data science job market since we launched SharpestMinds. We’ve interviewed thousands of aspiring data…
Towards Data Science
Mind the Machines: a podcast about data science jobs and the future of AI
We’ve learned a lot about the data science job market since we launched SharpestMinds. We’ve interviewed thousands of aspiring data…
🎥 Deep Learning на пальцах 10 - Recurrent Neural Networks
👁 1 раз ⏳ 5100 сек.
👁 1 раз ⏳ 5100 сек.
Курс: http://dlcourse.ai
Слайды: https://www.dropbox.com/s/eafd6z6sr2ajnka/Lecture%2010%20-%20RNNs%20-%20annotated.pdf?dl=0Vk
Deep Learning на пальцах 10 - Recurrent Neural Networks
Курс: http://dlcourse.ai Слайды: https://www.dropbox.com/s/eafd6z6sr2ajnka/Lecture%2010%20-%20RNNs%20-%20annotated.pdf?dl=0
Security Vulnerabilities of Neural Networks
🔗 Security Vulnerabilities of Neural Networks
What to do when your network thinks everything is an ostrich.
🔗 Security Vulnerabilities of Neural Networks
What to do when your network thinks everything is an ostrich.
Towards Data Science
Security Vulnerabilities of Neural Networks
What to do when your network thinks everything is an ostrich.
MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
🎥 MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
👁 1 раз ⏳ 4055 сек.
🎥 MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
👁 1 раз ⏳ 4055 сек.
Introductory lecture on Human-Centered Artificial Intelligence (MIT 6.S093) I gave on February 1, 2019. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.
INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/2IDMd0U
Transcript: http://bit.ly/2IDMkcQ
Playlist: http://bit.ly/deep-learnVk
MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
Introductory lecture on Human-Centered Artificial Intelligence (MIT 6.S093) I gave on February 1, 2019. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website…