https://github.com/shibasishb2/neural-network-and-deep-learning

Part A: To build a machine learning model to predict the signal quality of a communication equipment using various parameters. Part B: To develop a digit classifier using the Street View Housing Number (SVHN) dataset.
https://github.com/shibasishb2/neural-network-and-deep-learning

deep-learning image-recognition neural-networks tensorflow

Last synced: about 2 months ago
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Part A: To build a machine learning model to predict the signal quality of a communication equipment using various parameters. Part B: To develop a digit classifier using the Street View Housing Number (SVHN) dataset.

• Host: GitHub
• URL: https://github.com/shibasishb2/neural-network-and-deep-learning
• Owner: shibasishb2
• Created: 2024-03-17T07:22:52.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-07-29T13:10:59.000Z (5 months ago)
• Last Synced: 2024-07-29T16:43:15.155Z (5 months ago)
• Topics: deep-learning, image-recognition, neural-networks, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 715 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Neural-Network-and-Deep-Learning Project

Part A: The objective is to build a machine learning model to predict the signal quality of a communication equipment using various parameters. The project involves data import, understanding, preprocessing, and training a neural network classifier to achieve this goal.

Part B: The aim is to develop a digit classifier using the Street View Housing Number (SVHN) dataset. The project entails data import, exploration, visualization, preprocessing, and training a neural network classifier to accurately recognize digits in natural scene images captured by Google Street View.