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Machine Learning

Alibaba AI Achieves the World's Best Results for Two LiTS Challenge Tasks

Alibaba stood out from nearly 100 teams of scientists for accurately detecting liver nodules in the Liver Tumor Segmentation Challenge (LiTS Challenge).

Translating 100 Billion Words Every Day for E-Commerce with Alibaba Machine Translation

This article is an outline of Alibaba's machine translation capabilities, the machine translation challenges, strategies and how it impacts the e-commerce business scenario.

Introduction to Alibaba Cloud Intelligent Service Robot

In this article, we take a quick look at the history of chatbots, and introduce the features of Alibaba Cloud's Intelligent Service Robot.

QA Systems and Deep Learning Technologies – Part 1

QA systems can interpret a user's questions described in natural language and return concise and accurate matched answers by searching in the heterogeneous corpora or QA knowledge bases.

Predicting Heart Diseases with Machine Learning

Heart disease is a major cause of death, affecting over 1/3 of the world's population. This article illustrates how to build a heart disease predictio.

Understanding Human/Computer Symbiosis for Artificial Intelligence

In this article, we will talk about the main areas where humans and AI technology need to improve and how human/computer interaction is going to make way for AI applications.

Finding Public Data for Your Machine Learning Pipelines

This article discusses how and where you can find public data to use in machine learning pipelines that you can then use in a variety of applications.

Machine Learning Algorithms and Scikit-Learn

This tutorial looks at the Scikit-Learn library for machine learning and how you can use machine learning algorithms on Alibaba Cloud.

Project Showcase | Global Flight Delay Prediction Using Machine Learning

This project is from the team MnoL, which was awarded with the Third Prize in the Global AI Innovation Challenge 2021 - Intelligent Weather Forecast for Better life.

Basic Concepts and Architecture of a Recommender System

In this article, Alibaba technical expert Aohai introduces the basic concepts and architecture of an enterprise-level recommender system.

Friday Blog - Week 34 - Detecting Diabetes With PAI Studio

This week we're taking a look at PAI Studio, a drag-and-drop machine learning tool that makes it easy for anybody to build and train machine learning models.

AI Sports: Best Practices of Alibaba Sports in End Intelligence

This article explains the benefits of AI Sports and end intelligence.

The Secret Behind Taobao's AI-Powered Personalized Recommendations

This article introduces Alibaba's Artificial Intelligence Online Serving (AI OS) and the evolution of its technical architecture and practices.

Privileged Features Distillation at Taobao Recommendations

10 Alibaba Cloud experts discuss feature input in prediction tasks and using PFD to maximize privileged features, particularly with Taobao recommendations.

Self-Driving Databases Are the Future, Learn Why

In this blog, Feifei Li, President of Database Systems at Alibaba, shares his thoughts on how AI will play a huge role in business operations in the future.

Build a Personalized Recommendation System on Alibaba Cloud in Three Steps

This article explains how to build a personalized recommendation system by illustrating a news recommendation system using AnalyticDB for PostgreSQL.

The Network Architecture and Network Management System behind This Year's Double 11

This article takes a look at the network architecture and network management system that powered this year's Double 11.

Double 11 Logistics: Cainiao's Battle of "Billions of Parcels"

The solutions that Cainiao, Alibaba's Smart Logistics Network, created have helped make impossible possible, greatly accelerating deliveries during Double 11.

Alibaba Customer Services Assistant: Human-Machine Collaboration to Improve Efficiency

This article explores how Alibaba Customer Services Assistant makes human-machine collaboration an inclusive capability across the service industry to enhance the quality of customer service.

How to Improve User Participation: The Rise of Interactive Recommendations

This article describes how users interact with the recommendation systems. It demonstrates the implementation of the interactive recommendation through the weather vane model.