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- Open and Easy-to-Use Deep Learning Platform for Enterprise and Research
- Deep Learning 101 - Documentation - Code -PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use, efficient, flexible and scalable deep learning platform, which is originally developed by Baidu scientists and engineers for the purpose of applying deep learning to many products at Baidu. -
- -PaddlePaddle is designed to be easy to use. It provides an intuitive and yet flexible interface for loading data and specifying model structure.
-PaddlePaddle supports a wide range of neural network architectures and optimization algorithms. It is easy to configure complex models such as neural machine translation model with attention mechanism or complex memory connection.
-In order to unleash the power of heterogeneous computing resource, optimization occurs at different levels of PaddlePaddle, including computing, memory, architecture and communication.
-With PaddlePaddle, it is easy to use many CPUs/GPUs and machines to speed up your training. PaddlePaddle can achieve high throughput and performance via optimized communication.
-If you have any problems using PaddlePaddle, please contact paddle-dev@baidu.com.
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The convoluted neural network can identify the main object in the image and output the classification result
Using the LSTM network to analyze the positive and negative aspects of the commenter's emotions from IMDB film review
Analyze user characteristics, movie features, rating scores, predict new users' ratings for different movies
Provids an intuitive and flexible interface for loading data and specifying model structure.
Supports CNN, RNN and other neural network. Easy to configure complex models.
Efficient optimization of computing, memory, communications and architecture.
Easy to use many CPUs/GPUs and machines to speed up your training and handle large-scale data easily.
The convoluted neural network can identify the main object in the image and output the classification result
Using the LSTM network to analyze the positive and negative aspects of the commenter's emotions from IMDB film review
Analyze user characteristics, movie features, rating scores, predict new users' ratings for different movies
Provids an intuitive and flexible interface for loading data and specifying model structure.
Supports CNN, RNN and other neural network. Easy to configure complex models.
Efficient optimization of computing, memory, communications and architecture.
Easy to use many CPUs/GPUs and machines to speed up your training and handle large-scale data easily.
Open and Easy-to-Use Deep Learning Platform for Enterprise and Research
+ Deep Learning 101 + Documentation + Code +PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use, efficient, flexible and scalable deep learning platform, which is originally developed by Baidu scientists and engineers for the purpose of applying deep learning to many products at Baidu. +
+ +PaddlePaddle is designed to be easy to use. It provides an intuitive and yet flexible interface for loading data and specifying model structure.
+PaddlePaddle supports a wide range of neural network architectures and optimization algorithms. It is easy to configure complex models such as neural machine translation model with attention mechanism or complex memory connection.
+In order to unleash the power of heterogeneous computing resource, optimization occurs at different levels of PaddlePaddle, including computing, memory, architecture and communication.
+With PaddlePaddle, it is easy to use many CPUs/GPUs and machines to speed up your training. PaddlePaddle can achieve high throughput and performance via optimized communication.
+If you have any problems using PaddlePaddle, please contact paddle-dev@baidu.com.
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