Hands-on Deep Learning using Keras
Deep learning has been widely adopted in data science. A deep learning model learns to perform classification tasks directly from images, text or sound. The model is trained using a large set of labeled data and neural network architectures that contain many layers.
Keras is one of the most powerful and easy-to-use open-source libraries for developing and evaluating deep learning models. It is a high-level neural network API, capable of running on top of low-level library such as TensorFlow, Theano and CNTK. It enables fast experimentation through a high level, user-friendly, modular and extensible API. Keras code is portable and can be run on both CPU and GPU.
This workshop will provide hands-on exposure to implement deep learning models using Keras.
Outline/Structure of the Workshop
- An Overview of Keras Architecture
- Basic Steps with Keras
- Implementing Convolutional Neural Network
- Implementing Recurrent Neural Network
- Keras Tutorials and Examples
- Conclusion and Future Scope
After attending this workshop, attendees will be able to…
- Understand basics of Keras libraries.
- Create deep learning models using sequential as well as functional APIs of Keras.
- Develop deep learning based applications using Keras.
Students, faculty members, researchers and Industrialists whose areas of interest include deep learning.
Prerequisites for Attendees
- Basic knowledge of Machine Learning
- No experience with Keras or Python is required
schedule Submitted 1 month ago
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