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CNN in deep learning

Track :

Computer Science
Course Presenter :

Learn With Jay

Lessons no : 12

For Free Certificate After Complete The Course

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What will you learn in this course?
  • Design and implement convolutional neural networks for image recognition and classification tasks using Python and TensorFlow
  • Apply pooling, activation functions, and fully connected layers to optimize CNN performance in visual data analysis
  • Develop CNN architectures like VGG, ResNet, and Inception for advanced computer vision applications
  • Utilize data augmentation techniques to improve CNN model accuracy and robustness in real-world scenarios
  • Evaluate CNN models using performance metrics such as accuracy, precision, and recall for image processing tasks
  • Build face recognition and medical image analysis systems leveraging CNN deep learning techniques
  • Troubleshoot and fine-tune CNN models to enhance efficiency and accuracy in visual data tasks
  • Deploy trained CNN models for practical applications in object detection, medical imaging, and image classification

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  • You must have an account Register
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  • Watch at least 50% of Lesson Duration
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Lessons | 12


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Sahaya jincy.G 

Good
2025-10-20

Noor Rahman 

Very good
2025-10-05

Dhanush Kumar. S 

Good
2025-10-03

Himavardhan naga venkat 

Excellent
2025-09-30

Aswin M 

Overall I really like this class because all lectures,I really enjoyed this class and the format it was presented in, The experience of this class has being nothing but positive.
2025-09-04

Areeba Shaukat 

Amazing
2025-08-25

Ummadi Ushasree 

Good
2025-07-30

DOUAE CHAIBI 

Mindluster's CNN course is a solid free option for beginners, offering clear basics, hands-on projects (like image classification), and a certificate, but lacks depth in advanced topics (e.g., transfer learning) and interactive elements. It’s great for a quick intro, but pair it with other resources for mastery.
New chat
2025-07-13

Osama 

Nice
2025-07-02

Shradha S Naik 

It was a good experience
2025-05-31

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CNN in deep learning, in this course we will learn about CNN in deep learning course. Convolutional Neural Networks (CNNs) are a powerful type of neural network used primarily for image recognition, object detection, and visual data analysis. This course introduces you to the foundational concepts of CNNs including convolutional layers, pooling, activation functions, and fully connected layers. You’ll explore how CNNs work with image data and how to implement them using Python and popular libraries like TensorFlow and Keras. We’ll cover practical applications such as image classification, face recognition, and medical image processing. Additionally, the course dives into advanced architectures like VGG, ResNet, and Inception to demonstrate real-world use cases. Through hands-on projects, you will build and train CNN models, evaluate performance, and apply data augmentation techniques. By the end of this course, you will have the skills to design and deploy CNNs for a variety of computer vision tasks with confidence. Learn With Jay