Multi-Backend Deep Learning with Keras

Course

This course is designed for developers who want to integrate machine learning into their Python projects. It offers a high-level intuitive understanding of deep learning fundamentals and guides you through coding and training models using Multi-Backend Keras (formerly known as Keras Core)—a new version of Keras that allows users to interact with different popular backend frameworks such as TensorFlow, PyTorch, and JAX. After a brief demonstration of the Keras API, we'll go over what neural networks are and the principles behind training and evaluating them. Next, you'll learn how to leverage powerful deep learning frameworks through the user-friendly Multi-Backend Keras abstraction. Finally, you'll build your own increasingly-complex Keras image classifiers for a self-driving car use case.

Intermediate
3 hours
Last Updated February 6, 2024

Skills you'll learn:

Deep learningTransfer learning

Prerequisites:

Intermediate PythonNumPy

Intermediate

3 hours

Last Updated February 6, 2024

Skills you'll learn:

Deep learning • Transfer learning • Multi-Backend Keras

Prerequisites:

Intermediate Python • NumPy

Course Lessons

Lesson 1

Multi-Backend Deep Learning with Keras

This lesson is an introduction to Multi-Backend Keras. Learn neural network fundamentals, leverage TensorFlow, PyTorch, and JAX, and practice building GPT and image classification models with Keras.

Taught By The Best

Jesse Chan

Software Engineer

Jesse Chan is a Software Engineer and Machine Learning Researcher with notable experience in open-sourced projects like Keras and MLflow, and applying ML to finance. He's also led Python bootcamps and was a teaching assistant at Carnegie Mellon University, where he received his computer science degree.

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