- Join our CrowdChat about deep learning and Apache Spark to find out what’s going on in the world of Spark-and what’s coming up.
- The CrowdChat, hosted by @IBMBigData , will bring together subject matter experts who will focus on the latest tech and trends in deep learning as well as their overlap with Apache Spark.
- A CrowdChat simply organizes tweets into streams of conversation.
- You’ll even be able to vote for your favorite comments so that they can be featured more prominently in the conversation.
- If the event will be your first experience with CrowdChat, don’t worry.
In this CrowdChat, join 11 experts from inside and outside IBM as you take part in a group exploration of the issues and possibilities that arise at the conjunction of Apache Spark and deep learning.
Continue reading “CrowdChat: Deep learning and Apache Spark”
- NVIDIA TensorRT@” is a high performance neural network inference engine for production deployment of deep learning applications.
- Generate optimized, deployment-ready models for inference
- Define and implement unique functionality using the custom layer API
- Deploy neural networks in full (FP32) or reduced precision (INT8, FP16)
- TensorRT can be used to rapidly optimize, validate and deploy trained neural network for inference to hyperscale data centers, embedded, or automotive product platforms.
Continue reading “NVIDIA TensorRT”
- Deep learning course: Getting Started with the Caffe Framework
- Choose a deep learning framework from the list below, download the supported version of cuDNN and follow the instructions on the framework page to get started.
- Chainer is a deep learning framework that’s designed on the principle of define-by-run.
- Caffe is a deep learning framework made with expression, speed, and modularity in mind.
Read the full article, click here.
@GPUComputing: “New #cuDNN 5.1, 2.7x faster training of #deeplearning networks with 3×3 convolutions.”
The NVIDIA Deep Learning SDK accelerates widely-used deep learning frameworks such as Caffe, CNTK, TensorFlow, Theano and Torch as well as many other deep learning applications. Choose a deep learning framework from the list below, download the supported version of cuDNN and follow the instructions on the framework page to get started.
Deep Learning Frameworks