Community Blog Tips for Improving Deep Learning Experience

Tips for Improving Deep Learning Experience

In this article, we will introduce some tips for deep learning works with TensorFlow, GPU sharing and Caffe.

Deep learning is one of the hottest subtopics about artificial intelligence these years. In this article, we will introduce some tips for improving deep learning experience, such as improving cluster scheduling with GPU sharing and processing image classfication with tensorflow and Caffe.

Introduction to TensorFlow for Deep Learning

TensorFlow is an open source software library that uses data flow graphs for numeric computation. The nodes in the graphs represent mathematical operations, while the edges represent the multidimensional data arrays (aka tensors) that are passed between them. The flexible architecture allows you to deploy the computation to one or more CPUs or GPUs in your desktops, servers, or mobile devices using a single API.

The normal workflow of running a program in TensorFlow is as follows:

  1. Create a computation graph on any math operation of your choice that is supported by TensorFlow.
  2. Initialize variables.
  3. Create a session.
  4. Run the graph in the session.
  5. Close the session.

Empower Deep Learning with GPU Sharing for Cluster Scheduling

GPU sharing can optimizes the usage of GPU resources in a cluster, which will improve your experience for deep learning tasks.

GPU sharing for cluster scheduling is to let more model development and prediction services share GPU, therefore improving Nvidia GPU utilization in a cluster. This requires the division of GPU resources. GPU resources are divided by GPU video memory and CUDA Kernel thread. Generally, cluster-level GPU sharing is mainly about two things: Scheduling and Isolation.

How to Classify Images Using Tensorflow

The processing of unstructured image data involves the use of deep learning algorithms, in this article you will find an efficient solution with Tensorflow.

The experiment of creating an image recognition model using the deep learning framework TensorFlow in Alibaba Cloud Machine Learning Platform for AI may take about 30 minutes.

How to Use Caffe Deep Learning Framework for Image Classification

Caffe is a deep learning framework, with which you can complete image classification model training for deep learning by editing configuration files. In this blog, we will introduce how to process image classification with Caffe in Alibaba Cloud Machine Learning Platform for AI.

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