Providing deep learning algorithms for 100+ products
+An Easy-to-use, Efficient, Flexible and Scalable Deep Learning Platform
@@ -61,8 +61,8 @@Easy to use, efficient, flexible, and scalable
+Providing deep learning algorithms for 100+ products
The convoluted neural network can identify the main object in the image and output the classification result
+Using Convolutional Neural Networks (CNN) for image recognition and object detection
@@ -82,7 +82,7 @@Using the LSTM network to analyze the positive and negative aspects of the commenter's emotions from IMDB film review
+Using Recurrent Neural Network (RNN) for sentiment analysis
@@ -98,8 +98,8 @@Analyze user characteristics, movie features, rating scores, predict new users' ratings for different movies
+Using Deep Learning on recommendation systems to help users find items
@@ -109,7 +109,7 @@Provids an intuitive and flexible interface for loading data and specifying model structure.
+Provides an intuitive and flexible interface for loading data and specifying model structure.
Supports CNN, RNN and other neural network. Easy to configure complex models.
+Supports CNN, RNN and various variants and ease to configure complicated deep models.
Efficient optimization of computing, memory, communications and architecture.
+Provides extremely optimized operations, memory recycling, network communication.
Easy to use many CPUs/GPUs and machines to speed up your training and handle large-scale data easily.
+Ease to scale heterogeneous computing resource and storage to accelerate training process.
Easy to Learn and Use Distributed Deep Learning Platform
+An Easy-to-use, Efficient, Flexible and Scalable Deep Learning Platform
@@ -159,4 +159,4 @@