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Intro to ML: Language Processing

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Intro to ML: Language Processing

4 个小时 Introductory universal_currency_alt 13 个积分
It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.

完成此课程中的所有活动即可赢取一枚徽章。完成挑战任务、游戏和课程即可收集 Qwiklabs 中的徽章。集齐所有徽章,彰显您的技能!

  • 实验

    AI Platform:Qwik Start

    在本实验中,您将训练 TensorFlow 模型并将其部署到 AI Platform 以提供预测服务。欢迎观看以下这两个简短视频:通过 AI Platform 利用强大的机器学习技术AI Platform:Qwik Start - Qwiklabs 预览

  • 实验

    Google Cloud Speech API: Qwik Start

    The Google Cloud Speech API integrates speech recognition into dev apps; you can now send audio/receive a text transcription. Watch these short videos Powerful Speech Recognition Using Google Machine Learning and Google Cloud Speech: Qwik Start - Qwiklabs Preview

  • 实验

    Cloud Natural Language API: Qwik Start

    The Cloud Natural Language API lets you extract entities and perform sentiment and syntactic analysis on text. Watch these short videos Gain Valuable Insights from Text with Cloud Natural Language and Cloud Natural Language: Qwik Start - Qwiklabs Preview.

  • 实验

    Entity and Sentiment Analysis with the Natural Language API

    The Cloud Natural Language API lets you extract entities, and perform sentiment and syntactic analysis on a block of text. In this hands-on lab you’ll learn how to extract entities and sentiment from text using the Cloud Natural Language API.

  • 实验

    Speech to Text Transcription with the Cloud Speech API

    The Cloud Speech API lets you do speech to text transcription from audio files in over 80 languages. In this hands-on lab you’ll record your own audio file and send it to the Speech API for transcription.

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