​Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning">
Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning

🔗 Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning
Posted by Eleni Triantafillou, Student Researcher, and Vincent Dumoulin, Research Scientist, Google Research Recently, deep learning has...

​Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning">
Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning

🔗 Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning
Posted by Eleni Triantafillou, Student Researcher, and Vincent Dumoulin, Research Scientist, Google Research Recently, deep learning has...

​Linear Discriminant Analysis for Dimensionality Reduction in Python - Machine Learning Mastery

🔗 Linear Discriminant Analysis for Dimensionality Reduction in Python - Machine Learning Mastery
Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can result in a simpler predictive model that may have better performance when making predictions on new data. Linear Discriminant Analysis, or LDA for short, is a predictive modeling algorithm for multi-class classification. It can also be used as a dimensionality reduction technique,

​Linear Discriminant Analysis for Dimensionality Reduction in Python - Machine Learning Mastery

🔗 Linear Discriminant Analysis for Dimensionality Reduction in Python - Machine Learning Mastery
Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can result in a simpler predictive model that may have better performance when making predictions on new data. Linear Discriminant Analysis, or LDA for short, is a predictive modeling algorithm for multi-class classification. It can also be used as a dimensionality reduction technique,

​new paper, Truncated Quantile Critics, improves SOTA on MuJoCo by 20-30% ! With TF and PT code.


Video: https://youtu.be/idp4k1L9UhM
Project page: https://bayesgroup.github.io/tqc
Paper: https://arxiv.org/abs/2005.04269
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Truncated Quantile Critics



🎥 Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
👁 1 раз ⏳ 68 сек.
Video for "Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics" by A. Kuznetsov, P. Shvechikov, A. Grishin, D. Vetrov
Project page: https://bayesgroup.github.io/tqc
Paper: https://arxiv.org/abs/2005.04269
Code Tensorflow: https://github.com/bayesgroup/tqc
Code PyTorch: https://github.com/bayesgroup/tqc_pytorch

​new paper, Truncated Quantile Critics, improves SOTA on MuJoCo by 20-30% ! With TF and PT code.


Video: https://youtu.be/idp4k1L9UhM
Project page: https://bayesgroup.github.io/tqc
Paper: https://arxiv.org/abs/2005.04269
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Truncated Quantile Critics



🎥 Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
👁 1 раз ⏳ 68 сек.
Video for "Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics" by A. Kuznetsov, P. Shvechikov, A. Grishin, D. Vetrov
Project page: https://bayesgroup.github.io/tqc
Paper: https://arxiv.org/abs/2005.04269
Code Tensorflow: https://github.com/bayesgroup/tqc
Code PyTorch: https://github.com/bayesgroup/tqc_pytorch

​new paper, Truncated Quantile Critics, improves SOTA on MuJoCo by 20-30% ! With TF and PT code.


Video: https://youtu.be/idp4k1L9UhM
Project page: https://bayesgroup.github.io/tqc
Paper: https://arxiv.org/abs/2005.04269
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Truncated Quantile Critics



🎥 Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
👁 1 раз ⏳ 68 сек.
Video for "Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics" by A. Kuznetsov, P. Shvechikov, A. Grishin, D. Vetrov
Project page: https://bayesgroup.github.io/tqc
Paper: https://arxiv.org/abs/2005.04269
Code Tensorflow: https://github.com/bayesgroup/tqc
Code PyTorch: https://github.com/bayesgroup/tqc_pytorch

​Deep Demand Forecasting with Amazon SageMaker

🔗 Deep Demand Forecasting with Amazon SageMaker
Use Deep Learning for Demand Forecasting

​Deep Demand Forecasting with Amazon SageMaker

🔗 Deep Demand Forecasting with Amazon SageMaker
Use Deep Learning for Demand Forecasting

​Deep Demand Forecasting with Amazon SageMaker

🔗 Deep Demand Forecasting with Amazon SageMaker
Use Deep Learning for Demand Forecasting

​Detecting Weird Data: Conformal Anomaly Detection

🔗 Detecting Weird Data: Conformal Anomaly Detection
Weird data is important. Often in data science, the goal is to discover trends in the data. However, consider doctors looking at images of…

​Detecting Weird Data: Conformal Anomaly Detection

🔗 Detecting Weird Data: Conformal Anomaly Detection
Weird data is important. Often in data science, the goal is to discover trends in the data. However, consider doctors looking at images of…

​Detecting Weird Data: Conformal Anomaly Detection

🔗 Detecting Weird Data: Conformal Anomaly Detection
Weird data is important. Often in data science, the goal is to discover trends in the data. However, consider doctors looking at images of…

​Fine-tuning ResNet with Keras, TensorFlow, and Deep Learning

In this tutorial, you will learn how to fine-tune ResNet using Keras, TensorFlow, and Deep Learning.

https://www.pyimagesearch.com/2020/04/27/fine-tuning-resnet-with-keras-tensorflow-and-deep-learning/

Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Fine-tuning ResNet with Keras, TensorFlow, and Deep Learning - PyImageSearch
In this tutorial, you will learn how to fine-tune ResNet using Keras, TensorFlow, and Deep Learning.

​COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning - PyImageSearch

🔗 COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning - PyImageSearch
In this tutorial, you will learn how to train a COVID-19 face mask detector with OpenCV, Keras/TensorFlow, and Deep Learning.

​COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning - PyImageSearch

🔗 COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning - PyImageSearch
In this tutorial, you will learn how to train a COVID-19 face mask detector with OpenCV, Keras/TensorFlow, and Deep Learning.

​The statistical discovery that turned around the world

🔗 The statistical discovery that turned around the world
Featuring central limit theorem

​Место обучения в кибернетических системах

🔗 Место обучения в кибернетических системах
За машинное обучение замолвите слово Мы переживаем бум методов машинного обучения и может показаться, что нет такой задачи, которую не решила бы стомиллионслойн...

​NVIDIA Ampere Architecture In-Depth | NVIDIA Developer Blog

🔗 NVIDIA Ampere Architecture In-Depth | NVIDIA Developer Blog
Today, during the 2020 NVIDIA GTC keynote address, NVIDIA founder and CEO Jensen Huang introduced the new NVIDIA A100 GPU based on the new NVIDIA Ampere GPU architecture. This post gives you a look…

​Как организовать тестирование, чтобы ускорить и стабилизировать релизы продукта.Часть 1

🔗 Как организовать тестирование, чтобы ускорить и стабилизировать релизы продукта.Часть 1
Если командная работа не согласована, между отдельными участниками процесса и целыми командами постоянно будут происходить столкновения, а продукты компании или...