Audio Classification with TensorFlow

提供方
Coursera Project Network
在此免費的指導 項目中,您將:

Audio classification with TensorFlow

Creating spectrograms from raw audio data

在面試中展現此實踐經驗

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this guided project, we are going to create a deep learning model and train it to learn to classify audio files. Audio classification usually does not get the same kind of attention as image classification with deep learning - this could be because audio processing that is typically used in such scenarios is not as straight forward as image data. In this project, we will look at one such processing to convert raw audio into spectrograms before using them in a convolutional neural network. You will need prior programming experience in Python. Some experience with TensorFlow is recommended. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, convolutional neural networks, and optimization algorithms like gradient descent but want to understand how to use TensorFlow to classify audio. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

必備條件

Prior programming experience in Python. Conceptual understanding of Neural Networks. Prior experience with TensorFlow and Keras is recommended.

您要培養的技能

Deep LearningArtificial Neural NetworkAudio processingMachine LearningTensorflow

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction

  2. Setup

  3. Explore the Data

  4. Spectrogram

  5. Prepare the Data

  6. Create the Model

  7. Model Training

  8. Predictions

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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