Fashion retail at scale: To block or not to block
March 3, 2020
Jesus Manuel Pieiro gives you a glimpse into the challenges Inditex overcame in the transition of the ecommerce platform from monolithic to a microservices environment, oriented toward using event-driven nonblocking I/O technologies like Node.js. Jesus highlights the architectural decisions, technology, and tools that allowed the company to leverage the commercial growth in the years to come.
Navigating in stormy waters: An approach to traffic management with Istio
March 1, 2020
History repeats itself. Some years ago, software engineers started to implement frameworks to ease the development of software applications. Laurentiu Spilca walks you through how microservices are currently delivered and what Istio can do for you in regard to traffic management.
Deep Learning Toolkit for Splunk
February 24, 2020
The Deep Learning Toolkit for Splunk allows you to integrate advanced custom machine learning systems with the Splunk platform using TensorFlow 2.0, PyTorch and NLP libraries. Jupyter Lab Notebooks are providing data scientists and machine learning developers with an integrated experience from rapid prototyping to operationalising models in production. The app is freely available on splunkbase.
Introduction to Hilbert AutoML with TensorFlow Extended (TFX) at Yahoo! JAPAN
February 23, 2020
Hilbert is an AI framework that works with TensorFlow Extended (TFX) at Yahoo! JAPAN, which provides AutoML to create production-level deep learning models automatically. Hilbert is currently used by over 20 services of Yahoo! JAPAN. Shin-Ichiro Okamoto details how to achieve production-level AutoML and explores service use cases at Yahoo! JAPAN.
Deep learning with Horovod and Spark using GPUs and Docker containers
February 20, 2020
Today, organizations understand the need to keep pace with new technologies when it comes to performing data science with machine learning and deep learning, but these new technologies come with their own challenges. Thomas Phelan demonstrates the deployment of TensorFlow, Horovod, and Spark using the NVIDIA CUDA stack on Docker containers in a secure multitenant environment.
Executive Briefing: Unpacking AutoML
February 19, 2020
Paco Nathan outlines the history and landscape for vendors, open source projects, and research efforts related to AutoML. Starting from the perspective of an AI expert practitioner who speaks business fluently, Paco unpacks the ground truth of AutoMLtranslating from the hype into business concerns and practices in a vendor-neutral way.
Machine learning challenges at LinkedIn: Spark, TensorFlow, and beyond
February 18, 2020
From people you may know (PYMK) to economic graph research, machine learning is the oxygen that powers how LinkedIn serves its 630M+ members. Zhe Zhang provides you with an architectural overview of LinkedIns typical machine learning pipelines complemented with key types of ML use cases.
Start your engines: Making deep reinforcement learning accessible to all developers (sponsored by AWS)
February 18, 2020
Reinforcement learning is an advanced machine learning technique that makes short-term decisions while optimizing for a longer-term goal through trial and error. Ian Massingham dives into state-of-the-art techniques in deep reinforcement learning for a variety of use cases.
Apache Hadoop 3.x state of the union and upgrade guidance
February 16, 2020
Wangda Tan and Wei-Chiu Chuang outline the current status of Apache Hadoop community and dive into present and future of Hadoop 3.x. You'll get a peak at new features like erasure coding, GPU support, NameNode federation, Docker, long-running services support, powerful container placement constraints, data node disk balancing, etc. And they walk you through upgrade guidance from 2.x to 3.x.
Building an AI platform: Key principles and lessons learned
February 16, 2020
Moty Fania details Intels IT experience of implementing a sales AI platform. This platform is based on streaming, microservices architecture with a message bus backbone. It was designed for real-time data extraction and reasoning and handles the processing of millions of website pages and is capable of sifting through millions of tweets per day.