Overview
Context
Deep learning is the machine learning technique behind the most exciting capabilities in robotics, natural language processing, image recognition, and artificial intelligence. In this Introduction to Deep Learning in Python course offered by Data Camp, you’ll gain hands-on practical knowledge of how to apply your Python skills to deep learning with the Keras 2.0 library.
Explore Keras Models with a Library Contributor
Taught by ex-Google data scientist and Keras contributor, Dan Becker, this deep learning course explores neural network models and how you can generate predictions with them. The first chapters will grow your understanding of both forward and backward propagation and how they work in practice.
Keras library is a Python library that can help you develop and review deep learning models. Like many Python libraries, it's free, open-source and very user friendly. You’ll start by creating a Keras model and will learn how to compile, fit, and classify it before making predictions.
Delve Further into Deep Learning
This course is part of several machine learning and deep learning tracks, offering you clear pathways to build your skills and experience in this area once you’ve completed the introductory course, whether you want to complete a personal project or move towards a career as a Machine Learning Scientist.
Programme Structure
Chapters include:
- Basics of deep learning and neural networks
- Building deep learning models with keras
- Optimizing a neural network with backward propagation
- Fine-tuning keras models
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Campus Location
- New York City, United States
Disciplines
Artificial Intelligence View 127 other Short Courses in Artificial Intelligence in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prerequisites:
- Supervised Learning with scikit-learn
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions