Audio Classification with TensorFlow

Coursera Project Network
학습자는 이 무료 안내 프로젝트에서 다음을 수행하게 됩니다.

Audio classification with TensorFlow

Creating spectrograms from raw audio data

인터뷰에서 이 안내형 체험 보여주기

Clock2 hours
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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.

요구 사항

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

개발할 기술

Deep LearningArtificial Neural NetworkAudio processingMachine LearningTensorflow

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  1. Introduction

  2. Setup

  3. Explore the Data

  4. Spectrogram

  5. Prepare the Data

  6. Create the Model

  7. Model Training

  8. Predictions

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

자주 묻는 질문

자주 묻는 질문

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