This learning path is designed for anyone interested in getting familiar with and exploring deep learning topics. Currently, the learning path covers the fundamentals of deep learning, but will be enhanced in the future to cover supervised and unsupervised deep learning concepts.
Deep learning fundamentals
Discover how deep learning is related to machine learning, explore its fundamentals, and look at the advantages of using deep learning algorithms in certain applications.
Estimated time to complete
Approximately 2 hours.
With this learning path, you get:
- An understanding of deep learning concepts
- An understanding of deep learning architectures
- A comparison of deep learning frameworks
- How to enable Eager Execution in TensorFlow
- How to perform linear regression using TensorFlow
- How to create a Jupyter Notebook that contains Python code for defining logistic regression, then use TensorFlow to implement it
- An understanding of how to build neural networks without the help of the frameworks