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What you learn in Bank Defaulters using ANN ?

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ANN Model
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Keras
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Python
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Weights
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Biasis
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Activation

About this Free Certificate Course

The Artificial Neural Network (ANN) is a data-processing paradigm inspired by the brain. It learns by doing, just like people. An ANN is designed for a given purpose, such as pattern recognition or data classification, through a learning process. Learning entails making changes to the synaptic connections between neurons. Keras is a neural network library written in Python that runs on top of Theano or Tensorflow. It's quick, open-source, and easy to use. Keras just offers a high-level API, whereas it has both a low-level and a high-level API. As a result, integrating these two ideas. We will study a few principles like ANN Architecture, Weights, Biasis, Activation Functions, Back Propagation, and more in this video, as well as see demonstrations with examples.

Course Outline

Objective of The Course
Architecture of ANN
Weights , Biasis and Activation Functions
Loss Functions in Neural Networks
Back Propagation in Neural Networks
Gradient Descent
Keras Basic ANN Architecture - Demo
Dataset Overview and Model Framework
ANN Application Credit Data - Demo
What is Dead Neuron Problem?
Is Scaling necessary?

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Bank Defaulters using ANN

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