Implementation of a Neural Network in Keras
A neural network is a type of machine learning which models itself after the human brain, creating an artificial neural network that via an algorithm allows the computer to learn by incorporating new data.
The main objective is to develop a system to perform a classification task and predicting whether a person will get diabetes in the future or not based on few parameters like Glucose, Blood Sugar, BMI, Skin Thickess etc. using Keras - Module for creating ANNs
- ANNs have the ability to learn and model non-linear and complex relationships, which is really important because in real-life, many of the relationships between inputs and outputs are non-linear as well as complex
- ANNs can generalize — After learning from the initial inputs and their relationships, it can infer unseen relationships on unseen data as well, thus making the model generalize and predict on unseen data
- Unlike many other prediction techniques, ANN does not impose any restrictions on the input variables (like how they should be distributed)
- Classification Tasks
- Pattern Recognition
- Speech Recognition
- Image Recognitions
- Forecastings
Download and install the following module:
1)keras- pip install keras
Pranav Raikote