Keras is a high-level neural network API. It is developed and maintained by an AI researcher at Google, Francois Chollet.
It was released in the year 2015. It is used for deep learning and is a part of Tensorflow.
Keras is an extensible, simple and consistent API. It provides high scalability of computation and supports multiple backends and platforms.
Now, let’s dive deep into the roadmap of Keras!
Prerequisites: One must have a basic understanding of Python and deep learning concepts before starting with Keras.
Step1:
Begin with the installation of Keras in your PC and its backend configuration.
Step2:
Have an overview of deep learning.
Step3:
Understand Keras modules, layers, customized layers, and models.
Step4:
We are halfway done with Keras. Learn model compilation, model evaluation, and model prediction.
Step5:
Learn convolution neural network, regression prediction using MPL, and time series prediction using LSTM RNN.
Step6:
We are done with it. Keep making models using pre-trained models to become fluent in them.
