Build a Neural Network model with python notebook, (tensorflow, keras, scikitln) for preventing customer churn

Data science project for Deep learning.

Build a neural network-based classifier that can determine whether the customer will leave or not in the next 6 months.

Data Description

The case study is from an open-source dataset from Kaggle. The dataset contains 10,000 sample points with 14 distinct features such as CustomerId, CreditScore, Geography, Gender, Age, Tenure, Balance, etc.

Best Practices for Notebook :

• The notebook should be well-documented, with inline comments explaining the functionality of code and markdown cells containing comments on the observations and insights.

• The notebook should be run from start to finish in a sequential manner before submission.

• It is preferable to remove all warnings and errors before submission.

Criteria Points

Reading Dataset and Feature Elimination

- Read the dataset properly - Print the overview of the data (statistical summary, shape, info, etc) - Eliminate the unique features from the dataset with proper reasoning

Perform an Exploratory Data Analysis on the data

- Checked whether the dataset is balanced or not - Bivariate analysis - Use appropriate visualizations to identify the patterns and insights - Any other exploratory deep dive

Illustrate the insights based on EDA

-Key meaningful observations from Bivariate analysis

Data Pre-processing

- Split the target variable and predictors - Split the data into train and test - Rescale the data

Model building

- Build Neural Network

Model Performance Improvement

-Comment on which metric is right for model performance evaluation and why? - Find the optimal threshold using ROC-AUC or Precision-Recall curves - Comment on model performance - Can model performance be improved? check and comment - Build another model to implement these improvements - Include all the model which were trained to reach at the final one

Model Performance Evaluation

- Evaluate the model on different performance metrics and comment on the performance and scope of improvement

Conclusion and key takeaways

- Final conclusion about the analysis

Notebook overall

- Structure and flow - Well commented code

Evner: Python, Machine Learning (ML), Datasøgning, Statistikker, Deep Learning

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Om arbejdsgiveren:
( 7 bedømmelser ) Atlanta, United States

Projekt ID: #30563284

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