开课单位--微软
1
Using R for Scalable Data Science: Single Machines to Hadoop Spa0rk Clusters[将R用于可扩展数据科学:单机到Hadoop Spark集群]
Hang Zhang(微软) In this tutorial, we will demonstrate how to create scalable, end-to-end data analysis processes in R on single machines as well as in-database in SQL...
热度:21
Hang Zhang(微软) In this tutorial, we will demonstrate how to create scalable, end-to-end data analysis processes in R on single machines as well as in-database in SQL...
热度:21
2
Deep Embedding Forest: Forestbased Serving with Deep Embedding Features[深度嵌入森林:具有深度嵌入特征的基于森林的服务]
Ying Shan(微软) Deep Neural Networks (DNN) have demonstrated superior ability to extract high level embedding vectors from low level features. Despite the success, th...
热度:32
Ying Shan(微软) Deep Neural Networks (DNN) have demonstrated superior ability to extract high level embedding vectors from low level features. Despite the success, th...
热度:32
3
A Dirty Dozen: Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments[肮脏的一打:在线控制实验中十二个常见的度量解释陷阱]
Somit Gupta(微软) Online controlled experiments (e.g., A/B tests) are now regularly used to guide product development and accelerate innovation in software. Product ide...
热度:32
Somit Gupta(微软) Online controlled experiments (e.g., A/B tests) are now regularly used to guide product development and accelerate innovation in software. Product ide...
热度:32
4
CNTK - Microsoft’s open-source deep-learning toolkit[CNTK -微软的开源深度学习工具包]
Frank Seide;Amit Agarwal(微软) Train neural networks like Microsoft product groups! This talk will introduce the Computational Network Toolkit, or CNTK, Microsoft’s scalable o...
热度:36
Frank Seide;Amit Agarwal(微软) Train neural networks like Microsoft product groups! This talk will introduce the Computational Network Toolkit, or CNTK, Microsoft’s scalable o...
热度:36
5
Scalable R on Spark[Spark上的可扩展R]
John-Mark Agosta;Debraj GuhaThakurta(微软) R is one of the most popular languages in the data science, statistical and machine learning (ML) community. However, when it comes to scalable data a...
热度:24
John-Mark Agosta;Debraj GuhaThakurta(微软) R is one of the most popular languages in the data science, statistical and machine learning (ML) community. However, when it comes to scalable data a...
热度:24
6
7
From Code to Data: AI at Scale for Developer Productivity[从代码到数据:面向开发者生产力的大规模AI]
Neel Sundaresan(微软) The last decade has seen three great phenomena in computing – the rebirth of AI algorithms and AI hardware; the evolution of cloud computing and...
热度:32
Neel Sundaresan(微软) The last decade has seen three great phenomena in computing – the rebirth of AI algorithms and AI hardware; the evolution of cloud computing and...
热度:32
8
Applying the Delta method in metric analytics: A practical guide with novel ideas[在度量分析中应用德尔塔方法:一个具有新颖想法的实用指南]
Jiannan Lu(微软) During the last decade, the information technology industry has adopted a data-driven culture, relying on online metrics to measure and monitor busine...
热度:34
Jiannan Lu(微软) During the last decade, the information technology industry has adopted a data-driven culture, relying on online metrics to measure and monitor busine...
热度:34
9
The role of hierarchies in exploratory data mining[层次结构在探索性数据挖掘中的作用]
Raghu Ramakrishnan(微软) In a broad range of data mining tasks, the fundamental challenge is to efficiently explore a very large space of alternatives. The difficulty is two-f...
热度:25
Raghu Ramakrishnan(微软) In a broad range of data mining tasks, the fundamental challenge is to efficiently explore a very large space of alternatives. The difficulty is two-f...
热度:25
10
Planet-Scale Land Cover Classification With FPGAs[基于FPGA的全球土地覆盖分类]
Joseph Sirosh(微软) AI for Earth puts Microsoft’s cloud and AI tools in the hands of those working to solve global environmental challenges. Land cover mapping is p...
热度:39
Joseph Sirosh(微软) AI for Earth puts Microsoft’s cloud and AI tools in the hands of those working to solve global environmental challenges. Land cover mapping is p...
热度:39