Bank Loan Approval Prediction With Artificial Neural Nets

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estrelas
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Neste Projeto Guiado, você irá:

Understand the theory and intuition behind Deep Neural Networks

Build and train a deep learning model using Keras with Tensorflow 2.0 as a backend.

Assess the performance of trained model and ensure its generalization using various Key performance indicators.

Clock2 hours
BeginnerBásico
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

In this hands-on project, we will build and train a simple deep neural network model to predict the approval of personal loan for a person based on features like age, experience, income, locations, family, education, exiting mortgage, credit card etc. By the end of this project, you will be able to: - Understand the applications of Artificial Intelligence and Machine Learning techniques in the banking industry - Understand the theory and intuition behind Deep Neural Networks - Import key Python libraries, dataset, and perform Exploratory Data Analysis. - Perform data visualization using Seaborn. - Standardize the data and split them into train and test datasets.   - Build a deep learning model using Keras with Tensorflow 2.0 as a back-end. - Assess the performance of the model and ensure its generalization using various Key Performance Indicators (KPIs). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que você desenvolverá

Deep LearningArtificial Intelligence (AI)Machine LearningPython Programmingclassification

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  1. Task 1: Understand the problem statement and business case

  2. Task 2: Import Datasets and Libraries

  3. Task 3: Exploratory Data Analysis

  4. Task 4: Perform Data Visualization

  5. Task 5: Prepare the data to feed the model

  6. Task 6: Understand the theory and intuition behind Artificial Neural Networks

  7. Task 7: Build a simple Multi Layer Neural Network

  8. Task 8: Compile and train a Deep Learning Model

  9. Task 9: Assess the performance of the trained model

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

Perguntas Frequentes – FAQ

Perguntas Frequentes – FAQ

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