Welcome to a new age where intelligent machines can see and understand the world! This course, "Deep Learning - Convolutional Neural Networks," offers an accessible way to learn about Convolutional Neural Networks (ConvNets) using Python. ConvNets have revolutionized computer vision, enabling advancements like self-driving cars, automated medical image analysis, and facial recognition with near-human accuracy. This course will give you the skills needed to be part of this transformative field and contribute to creating the next generation of innovative applications.
By the end of this course, "Deep Learning - Convolutional Neural Networks," you'll have a solid understanding of ConvNets and their components, such as convolutional layers, pooling layers, and activation functions. You'll learn to design and implement ConvNets using popular deep learning libraries like TensorFlow. Additionally, you'll develop the ability to analyze and critique existing ConvNet designs and algorithms, understanding their strengths and weaknesses for different tasks.
This course, "Deep Learning - Convolutional Neural Networks," is your launchpad into Artificial Intelligence and Machine Learning. It provides the foundational skills and knowledge to help you navigate this exciting field. But remember, this is just the beginning. Keep exploring, learning, and diving deeper into this incredible frontier. Your journey into the world of AI and Machine Learning starts here!
Deep Learning - Convolutional Neural Networks Table of Contents:
- Introduction - 31:20
- Convolution Layer of ConvNet - 08:51
- Classical Neural Network LeNet - 12:37
- Classical Network - AlexNet - 11:15
- Neural Networks in Controls - 14:03
- Convolutional Neural Networks - Quick Overview - 22:07
- Convolutional Neural Networks - First Coding Example (Matlab) - 10:00
- Convolutional Neural Networks (CNNs) 1-Hour MCQ Assignment - 10 questions
- Coding NN with Python - 08:41
- TensorFlow Part I - 52:25
- TensorFlow Part II (Implementing MLP with Keras) - 49:34
- MCQ Based Test on Convolutional Neural Networks (CNNs) and TensorFlow - 5 questions
Who is this course for?
- Artificial Intelligence enthusiasts, software engineering students and professionals, electrical engineers, and even seasoned practitioners
Click on the links below to Download Deep Learning - Convolutional Neural Networks!
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