Alibaba has made its lightweight mobile-side deep learning inference engine, Mobile Neural Network (MNN), open source to benefit more app and IoT developers.
In this post, we 6 key automated machine learning (AutoML) platforms that can assist data scientists to accelerate machine learning development.
In Part 4 of this 4-article series, we will load the saved model again for extracting features from the datasets.
In Part 3 of this 4-article series, we are going to transfer the learning of MobileNet for working with the Fruits360 dataset.
In Part 2 of this 4-article series, we will create a Jupyter notebook and download the Fruits360 dataset using Keras within the Jupyter notebook.
In Part 1 of this 4-article series, we will explore the ML pipeline to highlight the challenges of manual feature extraction.
In this blog, we'll review useful tricks in deep learning and compile an optimization scheme called "checklist testing" that can upgrade any existing deep learning repository.
In this article, we discuss how Ali-Perseus can help create a highly optimized and unified distributed communication framework for deep learning on Alibaba Cloud.
This article forms the McKinsey's report on artificial intelligence (AI) as a basis to discuss the evolving field of AI and its diverse applications across multiple industries.
This brief tutorial shows you the step-by-step installation process for preparing cuDNN on an Alibaba Cloud GPU instance.
Alibaba Cloud ranked first in terms of image recognition performance and cost in Stanford University' latest DAWNBench deep learning inference rankings.
This tutorial teaches several ways you can install MXNet, the deep learning tool on Alibaba Cloud ECS running Ubuntu 16.04.
This article introduces a method of image recognition using deep learning that can be applied to image filtering, facial recognition, and object detection.
In this tutorial, we will make a pre-trained deep learning model named Word2Vec available to other services by building a REST API from the ground up.
In this article, Liu Lei talks about the applications of Image Search for e-commerce, developed by Alibaba's Machine Intelligence Technology Laboratory.
In this article, we will discuss Alibaba Group's innovative deep learning algorithms that help improve product recommendation accuracy.
Image compression and acceleration underpin most of the media applications in the consumer space. In this article, we will discuss how deep learning can improve these methods.
This article explores various forms of Attention Mechanisms in Natural Language Processing (NLP) and their applications in multiple areas such as machine translation tasks.
Alibaba's Infrastructure Service Group and the algorithm team from Machine Intelligence Technologies have successfully developed an ultra low latency .
Alibaba Cloud deep learning tool, Arena, helps data scientists run deep learning on the cloud without having to learn to manipulate low-level IT resources.
