Beginners Guide to Implementing Neural Networks with Keras
- Introduced to Colab by Google
- How to Implement Deep Neural Network
- How to Implement Convolutional Neural Network
- How to Implement Recurrent Neural Network
- How to Implement Complex Neural Network which has both CNN and RNN layers
- Student ought to grasp theoretical ideas of Deep Learning
- Some expertise with Python aiming to be|are} a plus
In this course, you’ll find out how to implement all major sorts of neural networks with active comes in Keras. you’ll not got to came upon something on your system, Everything will be done online. you’ll be supplied with Example code and apply problems. you’re going to do the subsequent projects
– Implement and train a completely connected neural network for MNIST dataset, character classification.
– Implement and train a Convolutional neural network for the MNISt dataset, character classification.
– Implement and train a Multi-Layer LSTM neural network for the WISDM dataset for act Recognition.
– Implement and train a Multi-Layer CNN-RNN quite neural network for the WISDM dataset for act Recognition.
For every of the projects, code is provided and Colab notebooks are shared that able to} experiment with. This course is intended in an exceedingly} thanks to start from the very basics and so reach a stage wherever you’ll be able to implement very recent and sophisticated models. it’s expected that you just have already got a theoretical background in deep learning a really basic data would be enough to induce started with this course. Hope you’ll just like the course and can get pleasure from following it.
Who this course is for:
- Beginners course for folks fascinated by learning the implementation of Neural Networks and doing planet comes.