Skill Track

Deep Learning in Python

In this track, you'll expand your deep learning knowledge and take your machine learning skills to the next level. Working with Keras and PyTorch, you’ll learn about neural networks, the deep learning model workflows, and how to optimize your models. You'll then use TensorFlow to build linear regression models and neural networks. Throughout the track, you'll use machine learning techniques to solve real-world challenges, such as predicting housing prices, building a neural network to predict handwritten numbers, and identify forged banknotes. By the end of the track, you'll be ready to use Keras to train and test complex, multi-output networks and dive deeper into deep learning.

  • Python
  • 20 hours
  • 5 courses
1
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Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.

4 hours
Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries

Instructors

Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries

Isaiah Hull

Economist

Ismail Elezi

Researcher PHD Student at Ca' Foscari University of Venice

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