Speaker: Anjuli Kannan

Software Engineer @GoogleBrain

Anjuli Kannan is a senior software engineer at Google. She is a member of the Brain Team, which works to advance the field of machine intelligence through a combination of basic research, software (TensorFlow), and applications that improve people's lives. Anjuli is especially interested applications of machine learning to problems in natural language understanding. Recently she was a core member of the team that brought the Smart Reply feature to Inbox by Gmail. Launched in 2015, Smart Reply was the first Google-scale application to effectively apply recurrent neural networks in language understanding, as well as the first to leverage Google's open-source TensorFlow.

Find Anjuli Kannan at

Talk : Deep Learning for Language Understanding (at Google Scale)

Tracks

  • Deep Learning Applications & Practices

    Deep learning lessons using tooling such as Tensorflow & PyTorch, across domains like large-scale cloud-native apps and fintech, and tacking concerns around interpretability of ML models.

  • Predictive Data Pipelines & Architectures

    Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Real-world Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.