Build A Dog/Cat Detector In C# With CNTK
I presented this webinar in 2019 for the students in my machine learning bootcamp.
In the webinar you’ll see me develop an object detector that uses a deep neural network to automatically categorize images of dogs and cats. I will build the neural network from scratch using the Microsoft Cognitive Toolkit.
1 ¾ Hours
English
Intermediate
Webinar Contents
Introducing Machine Learning
Current trends in AI
Jobs replaced by robots
Machine learning algorithms
The convolutional neural network
Building neural networks
The sandwich model
Convolution layers
Pooling layers
Dropout layers
Dense classification layers
The Dog & Cat Dataset
The folder structure
The dataset labels
Generating the mapping file
The C# Code
The CNTK library
The Pensar library
Building a neural network in C#
Adding convolution, pooling, dropout and dense network layers
Shaping the tensors
The C# Code (continued)
The Adam learner
The training loop
The testing loop
Demo: training the network
The Results
Overfitting
Data augmentation
Training and validation accuracy
Saving the trained model
Categorizing single images
Watch The Webinar
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Download The Source Code
Would you like to experiment with your own code? Just click the button to download the exact same source code that I use in the webinar. Use my code as a starting point to develop your own C# computer vision applications!
Testimonials
what my students are saying about ME
Michal Stankowski
AI Self-Paced Student
“Mark is a fantastic teacher with a deep understanding of his course topics, as well as broader technology / trends. The structure and pacing of Mark’s courses is excellent and he constantly relates the theory to practice.”
Phil Tomblin
AI Self-Paced Student
“Participating on such a well-taught course was an awesome experience. I love the fact that we can all learn and help each other at a global scale. Mark is a gifted teacher as well as amazing technically skilled”
Yoav Kaplan
AI Self-Paced Student
