🎥 Brief Moments of the AI Gold Rush | by Bing Xu | Kaggle Days SF
👁 3 раз ⏳ 2297 сек.
👁 3 раз ⏳ 2297 сек.
Bing Xu
"Brief Moments of the AI Gold Rush"
Kaggle Days San Francisco held in April 2019 gathered over 300 participants to meet, learn and code with Kaggle Grandmasters, and compete in our traditional offline competition.
This edition is presented by LogicAI with sponsorship from Kaggle and Google Cloud.
Kaggle Days are a global series of offline events for seasoned data scientists and Kagglers created by LogicAI and Kaggle.
About the presenter:
Bing is currently an Applied Research Scientist at FacebookVk
Brief Moments of the AI Gold Rush | by Bing Xu | Kaggle Days SF
Bing Xu
"Brief Moments of the AI Gold Rush"
Kaggle Days San Francisco held in April 2019 gathered over 300 participants to meet, learn and code with Kaggle Grandmasters, and compete in our traditional offline competition.
This edition is presented by LogicAI…
"Brief Moments of the AI Gold Rush"
Kaggle Days San Francisco held in April 2019 gathered over 300 participants to meet, learn and code with Kaggle Grandmasters, and compete in our traditional offline competition.
This edition is presented by LogicAI…
🎥 Deep Q learning is Easy in PyTorch (Tutorial)
👁 1 раз ⏳ 2055 сек.
👁 1 раз ⏳ 2055 сек.
Deep Q Learning w/ Pytorch: https://youtu.be/RfNxXlO6BiA
Where to find data for Deep Learning: https://youtu.be/9oW3WfKk6d4
#DeepQLearning #PyTorch #ReinforcementLearning
In this tutorial you will code up the simplest possible deep q network in PyTorch. We'll also correct some minor errors from previous videos, which were rather subtle.
You'll see just how easy it is to implement a deep Q network in Pytorch and beat the lunar lander environment. The agent goes from crashing on the lunar surface to landinVk
Deep Q learning is Easy in PyTorch (Tutorial)
Deep Q Learning w/ Pytorch: https://youtu.be/RfNxXlO6BiA
Where to find data for Deep Learning: https://youtu.be/9oW3WfKk6d4
#DeepQLearning #PyTorch #ReinforcementLearning
In this tutorial you will code up the simplest possible deep q network in PyTorch.…
Where to find data for Deep Learning: https://youtu.be/9oW3WfKk6d4
#DeepQLearning #PyTorch #ReinforcementLearning
In this tutorial you will code up the simplest possible deep q network in PyTorch.…
🎥 Tips and Tricks for Machine Learning | by Stanislav Semenov | Kaggle Days Paris
👁 1 раз ⏳ 1645 сек.
👁 1 раз ⏳ 1645 сек.
Stanislav Semenov
"Tips and tricks for Machine Learning"
Kaggle Days Paris was held in January 2019 and gathered over 200 participants to meet, learn and code with Kaggle Grandmasters, and compete in our traditional offline competition.
This edition is presented by LogicAI in partnership with Kaggle and sponsored by LVMH, Christian Dior, Sephora, and Louis Vuitton.
Kaggle Days are a global series of offline events for seasoned data scientists and Kagglers created by LogicAI and Kaggle.
About the preseVk
Tips and Tricks for Machine Learning | by Stanislav Semenov | Kaggle Days Paris
Stanislav Semenov
"Tips and tricks for Machine Learning"
Kaggle Days Paris was held in January 2019 and gathered over 200 participants to meet, learn and code with Kaggle Grandmasters, and compete in our traditional offline competition.
This edition is…
"Tips and tricks for Machine Learning"
Kaggle Days Paris was held in January 2019 and gathered over 200 participants to meet, learn and code with Kaggle Grandmasters, and compete in our traditional offline competition.
This edition is…
🎥 Lesson 7. Neural Networks training (part 2)
👁 1 раз ⏳ 2254 сек.
👁 1 раз ⏳ 2254 сек.
Mastering the Neural Networks requires a lot of practice, in this and in the previous video we discuss things that are important for training your NN effectively.
Lecturer: Tatiana Gaintseva (PSAMI MIPT, Yandex SDA)
Part 1:
https://youtu.be/Il_W4dO_69Y
Materials link:
https://drive.google.com/open?id=1eSHBRPr022KjH93GMXQyA5kQfqA1WUvu
---
About Deep Learning School at PSAMI MIPT
Official website: https://www.dlschool.org
Github-repo: https://github.com/DLSchool/dlschool_english
About PSAMI MIPT
OVk
Lesson 7. Neural Networks training (part 2)
Mastering the Neural Networks requires a lot of practice, in this and in the previous video we discuss things that are important for training your NN effectively.
Lecturer: Tatiana Gaintseva (PSAMI MIPT, Yandex SDA)
Part 1:
https://youtu.be/Il_W4dO_69Y…
Lecturer: Tatiana Gaintseva (PSAMI MIPT, Yandex SDA)
Part 1:
https://youtu.be/Il_W4dO_69Y…
Recurrence in biological and artificial neural networks
🔗 Recurrence in biological and artificial neural networks
Recurrence is an overloaded term in the context of neural networks, with disparate colloquial meanings in the machine learning and the…
🔗 Recurrence in biological and artificial neural networks
Recurrence is an overloaded term in the context of neural networks, with disparate colloquial meanings in the machine learning and the…
Towards Data Science
Recurrence in biological and artificial neural networks
Recurrence is an overloaded term in the context of neural networks, with disparate colloquial meanings in the machine learning and the…
🎥 Building our first Convolutional Neural Networks in Keras step by step
👁 1 раз ⏳ 1290 сек.
👁 1 раз ⏳ 1290 сек.
Welcome to Keras tutorial. In this tutorial we will:
1. Learn to use Keras, a high-level neural networks API (programming framework), written in Python and capable of running on top of several lower-level frameworks including TensorFlow.
2. See how you can in a couple of hours build a classification algorithm.
Why are we using Keras? Keras was developed to enable deep learning engineers to build and experiment with different models very quickly. Just as TensorFlow is a higher-level framework than Python,Vk
Building our first Convolutional Neural Networks in Keras step by step
Welcome to Keras tutorial. In this tutorial we will:
1. Learn to use Keras, a high-level neural networks API (programming framework), written in Python and capable of running on top of several lower-level frameworks including TensorFlow.
2. See how you can…
1. Learn to use Keras, a high-level neural networks API (programming framework), written in Python and capable of running on top of several lower-level frameworks including TensorFlow.
2. See how you can…
🎥 Kaggle Live Coding: Is it getting easier or harder to become a kernels expert? | Kaggle
👁 1 раз ⏳ 4154 сек.
👁 1 раз ⏳ 4154 сек.
Join Kaggle data scientist Rachael Tatman as she investigates whether it's getting easier or harder to become a kernels expert (or master or grandmaster!).
SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_...
About Kaggle:
Kaggle is the world's largest community of data scientists. Join us to compete, collaborate, learn, and do your data science work. Kaggle's platform is the fastest way to get started on a new data science project. Spin up a Jupyter notebook with a single click. Build with our huge reposVk
Kaggle Live Coding: Is it getting easier or harder to become a kernels expert? | Kaggle
Join Kaggle data scientist Rachael Tatman as she investigates whether it's getting easier or harder to become a kernels expert (or master or grandmaster!).
SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_...
About Kaggle:
Kaggle is the world's largest…
SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_...
About Kaggle:
Kaggle is the world's largest…
Python | Reading contents of PDF using OCR (Optical Character Recognition)
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
https://www.geeksforgeeks.org/python-reading-contents-of-pdf-using-ocr-optical-character-recognition/
🔗 Python | Reading contents of PDF using OCR (Optical Character Recognition) - GeeksforGeeks
Python is widely used for analyzing the data but the data need not be in the required format always. In such cases, we convert that… Read More »
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
https://www.geeksforgeeks.org/python-reading-contents-of-pdf-using-ocr-optical-character-recognition/
🔗 Python | Reading contents of PDF using OCR (Optical Character Recognition) - GeeksforGeeks
Python is widely used for analyzing the data but the data need not be in the required format always. In such cases, we convert that… Read More »
GeeksforGeeks
Python | Reading contents of PDF using OCR (Optical Character Recognition) - GeeksforGeeks
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🎥 Toward Unsupervised Learning of Speech Representations
👁 10 раз ⏳ 2828 сек.
🎥 Toward Unsupervised Learning of Speech Representations
👁 10 раз ⏳ 2828 сек.
In this presentation, I first introduce unsupervised/self-supervised learning. Then, I describe some of my recent works that aim to learn general and robust self-supervised speech representations.Vk
Toward Unsupervised Learning of Speech Representations
In this presentation, I first introduce unsupervised/self-supervised learning. Then, I describe some of my recent works that aim to learn general and robust self-supervised speech representations.
🎥 OpenAI Five Beats World Champion DOTA2 Team 2-0
👁 7 раз ⏳ 691 сек.
👁 7 раз ⏳ 691 сек.
Check out Lambda Labs here: https://lambdalabs.com/papers
OpenAI's blog post: https://openai.com/blog/openai-five-finals/
Reddit AMA: https://old.reddit.com/r/DotA2/comments/bf49yk/hello_were_the_dev_team_behind_openai_five_we/
Reddit discussion on buybacks: https://old.reddit.com/r/DotA2/comments/bcx8cf/i_think_the_openai_games_revealed_an_invisible/
🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
313V, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, AnthonyVk
OpenAI Five Beats World Champion DOTA2 Team 2-0
Check out Lambda Labs here: https://lambdalabs.com/papers
OpenAI's blog post: https://openai.com/blog/openai-five-finals/
Reddit AMA: https://old.reddit.com/r/DotA2/comments/bf49yk/hello_were_the_dev_team_behind_openai_five_we/
Reddit discussion on buybacks:…
OpenAI's blog post: https://openai.com/blog/openai-five-finals/
Reddit AMA: https://old.reddit.com/r/DotA2/comments/bf49yk/hello_were_the_dev_team_behind_openai_five_we/
Reddit discussion on buybacks:…
🎥 Tensorflow | SciPy Japan 2019 Tutorial | Josh Gordon, Amit Patankar
👁 1 раз ⏳ 7333 сек.
👁 1 раз ⏳ 7333 сек.
A hands-on introduction to TensorFlow 2.0. In this 3.5 hour tutorial, we will briefly introduce TensorFlow, then dive in to training neural networks. This tutorial is targeted at folks new to TensorFlow, and/or Deep Learning. Our goal is to help attendees get started efficiently and effectively, so they can continue learning on your own. Attendees will need a laptop with an internet connection, there is nothing to install in advance.
Prerequisites: Prior machine learning experience is not assumed. We will dVk
Tensorflow | SciPy Japan 2019 Tutorial | Josh Gordon, Amit Patankar
A hands-on introduction to TensorFlow 2.0. In this 3.5 hour tutorial, we will briefly introduce TensorFlow, then dive in to training neural networks. This tutorial is targeted at folks new to TensorFlow, and/or Deep Learning. Our goal is to help attendees…
TensorFlow Model Optimization Toolkit — Pruning API
🔗 TensorFlow Model Optimization Toolkit — Pruning API
Since we introduced the Model Optimization Toolkit — a suite of techniques that developers, both novice and advanced, can use to optimize…
🔗 TensorFlow Model Optimization Toolkit — Pruning API
Since we introduced the Model Optimization Toolkit — a suite of techniques that developers, both novice and advanced, can use to optimize…
Medium
TensorFlow Model Optimization Toolkit — Pruning API
Since we introduced the Model Optimization Toolkit — a suite of techniques that developers, both novice and advanced, can use to optimize…
🎥 The Pattern Machine (What is Deep Learning?)
👁 1 раз ⏳ 650 сек.
👁 1 раз ⏳ 650 сек.
Part 1 of a series on Artificial Intelligence. Introduces the field of Deep Learning and the idea of distributed representations. The next videos will go deeper...Vk
The Pattern Machine (What is Deep Learning?)
Part 1 of a series on Artificial Intelligence. Introduces the field of Deep Learning and the idea of distributed representations. The next videos will go deeper...
The Binary Extremes of Daenerys Targaryen
https://towardsdatascience.com/the-binary-extremes-of-daenerys-targaryen-1c89502de92d
🔗 The Binary Extremes of Daenerys Targaryen
(Or should I say… “The Binary ExTREEmes”?)
https://towardsdatascience.com/the-binary-extremes-of-daenerys-targaryen-1c89502de92d
🔗 The Binary Extremes of Daenerys Targaryen
(Or should I say… “The Binary ExTREEmes”?)
Towards Data Science
The Binary Extremes of Daenerys Targaryen
(Or should I say… “The Binary ExTREEmes”?)
Geometric Deep Learning for Pose Estimation
🔗 Geometric Deep Learning for Pose Estimation
Theory and Pytorch Implementation Tutorial to find Object Pose from Single Monocular Image
🔗 Geometric Deep Learning for Pose Estimation
Theory and Pytorch Implementation Tutorial to find Object Pose from Single Monocular Image
Medium
Geometric Deep Learning for Pose Estimation
Theory and Pytorch Implementation Tutorial to find Object Pose from Single Monocular Image
🎥 Deep Web: A Web Cmdlets Deep Dive by Mark Kraus
👁 1 раз ⏳ 5136 сек.
👁 1 раз ⏳ 5136 сек.
With many IT processes moving to REST based APIs and our ever increasing reliance on websites to do our jobs as developers and operators, never has there been a time more critical for learning all there is to know as much as possible about the Web Cmdlets. Invoke-WebRequest is like a web browser in your PowerShell console and Invoke-RestMethod converts a remote API endpoint into a PowerShell object.
Go beyond the -Uri parameter and explore the rich and numerous features of these Cmdlets. Learn what sessionVk
Deep Web: A Web Cmdlets Deep Dive by Mark Kraus
With many IT processes moving to REST based APIs and our ever increasing reliance on websites to do our jobs as developers and operators, never has there been a time more critical for learning all there is to know as much as possible about the Web Cmdlets.…
🎥 Machine Learning Part 18: Boosting Algorithms — Gradient Boosting In Python
👁 1 раз ⏳ 670 сек.
👁 1 раз ⏳ 670 сек.
In this video, we walk through the gradient boosting algorithm and implement it in Python.
CONNECT
Site: https://coryjmaklin.com/
Medium: https://medium.com/@corymaklin
GitHub: https://github.com/corymaklin
Twitter: https://twitter.com/CoryMaklin
Linkedin: https://www.linkedin.com/in/cory-maklin-a51732b7/
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Patreon: https://www.patreon.com/corymaklinVk
Machine Learning Part 18: Boosting Algorithms — Gradient Boosting In Python
In this video, we walk through the gradient boosting algorithm and implement it in Python. CONNECT Site: https://coryjmaklin.com/ Medium: https://medium.com/@corymaklin GitHub: https://github.com/corymaklin Twitter: https://twitter.com/CoryMaklin Linkedin:…
DeepFool — A simple and accurate method to fool deep Neural Networks.
🔗 DeepFool — A simple and accurate method to fool deep Neural Networks.
An Adversarial Attack
🔗 DeepFool — A simple and accurate method to fool deep Neural Networks.
An Adversarial Attack
Towards Data Science
DeepFool — A simple and accurate method to fool Deep Neural Networks.
An Adversarial Attack