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- Level: Intermediate
- Duration: 01h 30m 43s
- Release date: 2022-04-08
- Author: Pratheerth Padman
- Provider: Pluralsight
Implement Image Recognition with a Convolutional Neural Network
Description
Content
Image recognition is used in a wide variety of ways in our daily lives. This course will teach you how to tune and implement convolutional neural networks in order to implement image recognition and classification on a business case.
- Course Overview02m
- Course Overview02m
- Exploring and Preparing a Dataset for Image Recognition24m
- Course and Module Introduction03m
- What Are We Trying to Solve?03m
- Demo: Setting up Your Environment03m
- Demo: Organizing the Dataset05m
- Demo: Exploring the Dataset03m
- Demo: Preprocessing and Preparing the Dataset06m
- Summary and Up Next01m
- Training a Convolutional Neural Network to Classify Images27m
- Module Introduction01m
- What Are Convolutional Neural Networks?02m
- CNN: Convolutions05m
- CNN: Activation05m
- CNN: Pooling02m
- CNN: Classification01m
- Demo: Creating the CNN Architecture05m
- Demo: Training the Model02m
- Demo: Performance Metrics – How Well Did Your Model Do?03m
- Summary and Up Next01m
- Improving Performance of the Convolutional Neural Network34m
- Module Introduction01m
- Better Performance – When and How?02m
- Procuring Additional Training Data – Image Augmentation05m
- Hyperparameter Tuning03m
- Overfitting and Underfitting03m
- Demo: Image Augmentation and Hyperparameter Tuning08m
- What Is Transfer Learning?04m
- Transfer Learning – When and How?04m
- Demo: Improving Performance through Transfer Learning03m
- Summary01m
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