Deep Learning

Azure Machine Learning Notebook VM の 3 つの特長


データ サイエンティストの職務は絶えず変化します。そのため、高速かつ柔軟な環境が必要になる一方で、組織のセキュリティ ポリシーやコンプライアンス ポリシーに従う必要もあります。2019 年 5 月に発表された Notebook Virtual Machine (VM) は、そうした相反する要件を満たすと同時に、データ サイエンティストのエクスペリエンス全体を簡素化します。

Principal Program Manager, Azure Machine Learning

Build your own deep learning models on Azure Data Science Virtual Machines


As a modern developer, you may be eager to build your own deep learning models, but aren’t quite sure where to start. If this is you, I recommend you take a look at the deep learning course from This new course helps software developers start building their own state-of-the-art deep learning models.

Principal Program Manager, Microsoft

Training a neural network to play Hangman without a dictionary


We used reinforcement learning and CNTK to train a neural network to guess hidden words in a game of Hangman. Our trained model has no reliance on a reference dictionary: it takes as input a variable-length, partially-obscured word (consisting of blank spaces and any correctly-guessed letters) and a binary vector indicating which letters have already been guessed. In the git repository associated with this post, we provide sample code for training the neural network and deploying it in an Azure Web App for gameplay.

Data Scientist II

From “A PC on every desktop” to “Deep Learning in every software”


Deep learning is behind many recent breakthroughs in Artificial Intelligence, including speech recognition, language understanding and computer vision. At Microsoft, it is changing customer experience in many of our applications and services, including Cortana, Bing, Office 365, SwiftKey, Skype Translate, Dynamics 365, and HoloLens.

Corporate Vice President, Artificial Intelligence & Research