Introduction to Image Classification with Python: A Beginner

Introduction to Image Classification with Python: A Beginner, available at Free, has an average rating of 4.87, with 22 lectures, based on 23 reviews, and has 487 subscribers.

You will learn about Fundamentals of Image Classification: Understand the basics of image classification, including what it is and its various applications. Data Preprocessing Techniques: Learn how to preprocess image data, including normalization, one-hot encoding, and splitting data into training and validation se Building and Training Convolutional Neural Networks (CNNs): Build, train, and evaluate CNN models using Keras, and understand how to fine-tune and optimize mode Handling Imbalanced Data: Apply techniques to manage imbalanced datasets to improve model fairness and accuracy. This course is ideal for individuals who are This course is designed for absolute beginners who are interested in learning about image classification using Python. It's ideal for students, hobbyists, and professionals who want to gain foundational skills in deep learning. It is particularly useful for This course is designed for absolute beginners who are interested in learning about image classification using Python. It's ideal for students, hobbyists, and professionals who want to gain foundational skills in deep learning.

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Summary

Title: Introduction to Image Classification with Python: A Beginner

Price: Free

Average Rating: 4.87

Number of Lectures: 22

Number of Published Lectures: 22

Number of Curriculum Items: 22

Number of Published Curriculum Objects: 22

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

• Fundamentals of Image Classification: Understand the basics of image classification, including what it is and its various applications.
• Data Preprocessing Techniques: Learn how to preprocess image data, including normalization, one-hot encoding, and splitting data into training and validation se
• Building and Training Convolutional Neural Networks (CNNs): Build, train, and evaluate CNN models using Keras, and understand how to fine-tune and optimize mode
• Handling Imbalanced Data: Apply techniques to manage imbalanced datasets to improve model fairness and accuracy.

Who Should Attend

• This course is designed for absolute beginners who are interested in learning about image classification using Python. It's ideal for students, hobbyists, and professionals who want to gain foundational skills in deep learning.

Target Audiences

• This course is designed for absolute beginners who are interested in learning about image classification using Python. It's ideal for students, hobbyists, and professionals who want to gain foundational skills in deep learning.