Deep Learning with Python
This title is part of the Python Mini-Degree – 13 Courses to Learn and Master Python
In this course we’ll be building a Convolutional Neural Network to classify hand-written digits. By using this neural network we’ll achieve a higher accuracy in this classification compared to that of a normal neural network. The way this network works is by using convolutions and filters, where the values of the kernels of our filters are actually learned by the program.
- Deep Learning
- Convolutional Neural Networks
- Convolutional Layer
- Pooling Layer
- Hyperparameter Tuning
- Visualizing convolution
This is the last and most advanced course of the Python Mini-Degree, and it builds on the topics and concepts covered in the previous courses.
About the Python Mini-Degree
The Python Mini-Degree is a bundle of 13 online video courses, that go all the way from teaching you how to code in Python while making a game, to building your own Artificial Intelligence (AI) and Internet of Things (IoT) applications using Computer Vision, Machine Learning and Deep Learning.
Learn more and enroll HERE.
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This course builds up on the concepts covered in our course Create a Handwriting Recognition AI with TensorFlow.
Python 3 is used in this course.
It is recommended to take this course as part of the Python Mini-Degree, which includes 12 courses on Python, Computer Vision, Machine Learning, Deep Learning and much more.
- Lifetime, 24/7 access
- Professional-grade video lessons
- Certificate of completion
- Closed captions