Deep Learning with Python

Deep Learning with Python


Product Description

This title is part of the Python Mini-Degree – 12 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.

Learning goals:

  • Deep Learning
  • Convolutional Neural Networks
    • Convolutional Layer
    • Pooling Layer
    • Architectures
  • 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 12 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.


Course Requirements

This course builds up on the concepts covered in our course Create a Handwriting Recognition AI with TensorFlow.

You need to have Python 2.7 installed.

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.