Watch Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python) Video Tutorial


Tutorial Details & Info

Tutorial Title: Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python)
Instructor / Channel: codebasics
Lesson Runtime: 15:30 Minutes
Publish Date: August 02, 2026
Total Students / Views: 873,679 views

Watch and learn Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python) presented by codebasics. The total lesson runtime is 15:30 minutes with detailed practical demonstrations. Access this full online lesson without any subscription or sign-up required.

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Course Description & Lesson Notes

Official Video Description:

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Learn how to apply Image Classification Using CNN (CIFAR10 Dataset) | Deep Learning Tutorial 24 (Tensorflow & Python) with this complete video tutorial guide. In this video, you will learn essential skills for Image Classification Using CNN (CIFAR10 Dataset) | Deep Learning Tutorial 24 (Tensorflow & Python).

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python) taught by codebasics. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

💡 Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python).
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by codebasics with real-world examples.
  • Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
  • Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.

📋 Recommended Prerequisites & Study Notes:

No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.

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