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By using Tensorflow Keras. Converting urbansound8k dataset to spectrogram images with librosa. Then preprocess(normalize,resize,grayscale) the images for training. Creating a CNN model and train model with results.

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artifical-intelligence cnn deep-learning keras-tensorflow librosa neural-networks python3

urbansound_classification's Introduction

๐Ÿ’ซ About Me:

๐Ÿ‘‹ Hi, Iโ€™m Arda
๐ŸŽ“ I graduated in Computer Engineering(100% English) with a 3.29 Cumulative GPA
๐Ÿ‘€ Iโ€™m interested in Artificial Intelligence, Mobile App Development, and Front-End Development
๐ŸŒฑ Iโ€™m working on React-native for cross-platform mobile app development and HTML,CSS,React.js for front-end development

Right now, I am working as a React Native developer with 1.5 years of experience.
I am open to new job opportunities.

I published my apps to the Google Play Store:
https://play.google.com/store/apps/details?id=com.nationalitychecker
https://play.google.com/store/apps/details?id=com.randomjokegenerator
https://play.google.com/store/apps/details?id=com.masterqrcode

๐ŸŒ Socials:

LinkedIn

๐Ÿ’ป Tech Stack:

React Native Java JavaScript Python C# Expo NPM Postgres Adobe Audition Adobe Photoshop Adobe Premiere Pro Keras NumPy Pandas TensorFlow scikit-learn

๐Ÿ“Š GitHub Stats:



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