Ten Techniques Learned From fast.ai Right now, Jeremy Howard – the co-founder of fast.ai – currently holds the 105th highest score for the plant seedling classification contest on Kaggle, but he's dropping fast. Why? His own students are beating him. And their names can now be found across the tops of leaderboards all over Kaggle. Right now, Jeremy Howard – the co-founder of fast.ai – currently ho
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This project contains an overview of recent trends in deep learning based natural language processing (NLP). It covers the theoretical descriptions and implementation details behind deep learning models, such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and reinforcement learning, used to solve various NLP tasks and applications. The overview also contains a summary o
Facebook accelerates AI development with new partners and production capabilities for PyTorch 1.0 Earlier this year, we shared a vision for making AI development faster and more interoperable. Today, during our first-ever PyTorch Developer Conference, we are announcing updates about the growing ecosystem of software, hardware, and education partners that are deepening their investment in PyTorch.
Pytorch tutorial DataSetの作成 DataLoader 自作transformsの使い方 PILの使い方 Model Definition Training total evaluation each class evaluation CNNを用いた簡単な2class分類をしてみる Pytorch tutorial Training a Classifier — PyTorch Tutorials 1.4.0 documentation Transfer Learning for Computer Vision Tutorial — PyTorch Tutorials 1.4.0 documentation Writing Custom Datasets, DataLoaders and Transforms — PyTorch Tutorials 1.4.0 doc
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Department of Computer Science University of Toronto jasper@cs.toronto.edu Hugo Larochelle Department of Computer Science University of Sherbrooke hugo.larochelle@usherbrooke.edu Ryan P. Adams School of Engineering and Applied Sciences Harvard University rpa@seas.harvard.edu Abstract The use of machine learning algorithms
Wednesday December 26, 2018 Gaussian Processes have a mystique related to the dense probabilistic terminology that's already evident in their name. But Gaussian Processes are just models, and they're much more like k-nearest neighbors and linear regression than may at first be apparent. Gaussian Processes have applications ranging from finding gold to optimizing hyperparameters of other models. Th
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