Tag: Deep Learning

Feed: What's New. Faster training with optimized TensorFlow 1.11 The Deep Learning AMIs now come with an optimized build of TensorFlow 1.11, custom-built from source to accelerate deep learning applications on Amazon EC2 C5 and P3 instances. For Amazon EC2 C5 instances, Deep Learning AMIs deploy compute-optimized TensorFlow built with Intel Advanced Vector Extensions (AVX instruction sets) to speed up the performance of vector and floating point operations. The AMIs also come pre-configured to leverage Intel Math Kernel Library for Deep Neural Networks (MKL-DNN). Training a ResNet-50 benchmark with the synthetic ImageNet dataset using our optimized build of TensorFlow 1.11 on ... Read More

Feed: R-bloggers. Author: Dr. Shirin Glander. During my stay in London for the m3 conference, I also gave a talk at the R-Ladies London Meetup on Tuesday, October 16th, about one of my favorite topics: Interpretable Deep Learning with R, Keras and LIME. Keras is a high-level open-source deep learning framework that by default works on top of TensorFlow. Keras is minimalistic, efficient and highly flexible because it works with a modular layer system to define, compile and fit neural networks. It has been written in Python but can also be used from within R. Because the underlying backend can ... Read More

Feed: SAS Blogs. Author: Wayne Thompson. Deep learning has taken off because organizations of all sizes are capturing a greater variety of data and can mine bigger data, including unstructured data.  It’s not just large companies like Amazon, SAS and Google that have access to big data. It’s everywhere. Deep learning needs big data, and now we have it. Another reason deep learning is revitalizing AI is that it provides a universal set of algorithms that can be applied to many use cases and applications, including: Conversational assistants on your cell phone likely use a recurrent neural network (RNN) to ... Read More

Feed: Hortonworks Blog – Hortonworks. Author: Saumitra Buragohain. What is a Data Science and Engineering Platform Apache Spark is one of our most popular workloads- both on-premises and cloud. As we recently announced HDP 3.0.0  (followed by a hardened HDP 3.0.1), we want to introduce the Data Science and Engineering Platform powered by Apache Spark. As noted in the marketecture above, our Data Science & Engineering Platform is powered by Apache Spark with Apache Zeppelin notebooks to enable Batch, Machine Learning, and Streaming use cases, by personas such as Data Engineers, Data Scientists and Business Analysts. We recently introduced Apache ... Read More

Feed: Microsoft Azure Blog. Author: Faith Xu. We are excited to release the preview of ONNX Runtime, a high-performance inference engine for machine learning models in the Open Neural Network Exchange (ONNX) format. ONNX Runtime is compatible with ONNX version 1.2 and comes in Python packages that support both CPU and GPU to enable inferencing using Azure Machine Learning service and on any Linux machine running Ubuntu 16. ONNX is an open source model format for deep learning and traditional machine learning. Since we launched ONNX in December 2017 it has gained support from more than 20 leading companies in ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  Advanced analytics and AI are the fourth great lever available to create organic improvement in corporations.  We’ll describe why this one is different from the first three and why the CEO needs the direct help of data scientists to make this happen.   If you’re a CEO or any other flavor of top executive leading a large company (or if you’re a data scientists trying to help one) then the mission to create continuous improvement is obvious.  Ultimately you probably think about this in terms of EBITDA or ... Read More

Feed: AWS Compute Blog. Author: Betsy Chernoff. Contributed by Sandy Carter, Vice President of Windows on AWS and Enterprise WorkloadsHappy birthday to all of our AWS customers! In particular, I want to call out Autodesk, RightScale (now part of Flexera), and Suunto (Movescount) – just a few of our customers who have been running Microsoft Windows Server and Microsoft SQL Server on AWS for 10 years! Thank you for your business and seeing the value of Windows on AWS! So many customers trust their Windows workloads on AWS because of our experience, reliability, security, and performance. IDC (a leading IT Analyst) estimates that ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vik Kumar. Given the touting of recent analytic and machine learning results in healthcare, why haven't doctors been replaced by computers yet? The truth is that there are many obstacles that stand in the way of implementing  analytics in healthcare. Ethical issues introduced by this technology are also fiercely debated and must be considered. Finally, while obstacles imply a possibility of being overcome, there are also limitations to this technology, or aspects that likely will not be solved anytime soon. Let's discuss all three of these things in this section. What ... Read More

Feed: R-bloggers. Author: Dr. Shirin Glander. These are my sketchnotes for Sam Charrington’s podcast This Week in Machine Learning and AI about Evaluating Model Explainability Methods with Sara Hooker: Sketchnotes from TWiMLAI talk: Evaluating Model Explainability Methods with Sara Hooker You can listen to the podcast here. In this, the first episode of the Deep Learning Indaba series, we’re joined by Sara Hooker, AI Resident at Google Brain. I had the pleasure of speaking with Sara in the run-up to the Indaba about her work on interpretability in deep neural networks. We discuss what interpretability means and when it’s important, ... Read More

Feed: R-bloggers. Author: STATWORX. STATWORX welcomes you to our open workshop “Deep Learning in R and Keras” ! The workshop is designed for advanced R-users who are fluent in importing, processing and manipulating data. The workshop will be held in german at our office in Frankfurt.You will learn how to construct, estimate and evaluate both basic and more complex neural networks in R and Keras. There is a limit of 8 persons per workshop to respond to every participant in the best possible way.If you want to read more about Deep Learning check out the blog post of our trainer ... Read More