Amp up your technical career with this Deep Learning Projects – Convolutional Neural Network Course. This course includes end-to-end procedures for implementing and stacking CNN in a deep network to solve multi-class image classification problems. CNN is a deep-learning algorithm that helps extract information from images. The course will provide a detailed overview of convolution neural networks in deep learning. It will refine your ability to implement convolutional neural networks for different real-time applications. The course will give you valuable insights into different CNN structures. It will explain how to prepare datasets for the CNN model. We’ll introduce you to the library used for the CNN model. You’ll recognise the different layers of the CNN and the steps involved in coding a convolutional neural network. Furthermore, you’ll understand data processing and augmentation in CNN. The course will demonstrate how a data generator works. Again, it will explain how to predict a single image. Finally, the course will explain model accuracy in deep learning and discuss the different types of CNN models.
Learning outcome
Convolutional Neural Networks: Learn the basics.
Learn how to apply CNNs for a variety of purposes.
Recognise that deep learning models depend heavily on accuracy.
Gain knowledge about CNN architecture optimisation and tuning.
Investigate cutting-edge methods to improve model functionality.
Obtain expertise to develop and produce fresh approaches to deep learning.
Use deep learning to accomplish projects that have the potential to change the world.
Get to know the wide range of applications for which Convolutional Neural Networks can be used.
Get experience by working on projects.
Develop your deep learning model optimisation talents.
Gain cutting-edge expertise to advance your career in machine learning and artificial intelligence.
Career Path
AI Engineer
Machine Learning Researcher
Data Scientist
Computer Vision Engineer
Deep Learning Specialist
Research Scientist
Neural Network Developer
Requirements
Basic understanding of Python programming.
Familiarity with machine learning concepts.
Access to a computer with internet connectivity.
Course Curriculum
Course Curriculum
Section 01: Introduction
Introduction of Project1
00:04:00
Overview of CNN
00:05:00
Section 02: Installations
Installations and Dataset Structure
00:11:00
Section 03: Getting Started
Import libraries
00:07:00
CNN Model and Layers Coding
00:10:00
Data Preprocessing and Augmentation
00:07:00
Section 04: Accuracy
Understanding Data generator
00:08:00
Prediction on Single Image
00:06:00
Understanding Different Models and Accuracy
00:06:00
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