Welcome to my GitHub portfolio!
I have completed several online courses and tutorials on data processing techniques and data analysis. In addition, I have practiced my learning in several small projects and demonstrated my ability to use various tools and technologies in data processing and analysis.
- Payment Default Prediction: Develop predictive models that can be used to identify customers who are at risk of cancellation of payments and help companies take appropriate countermeasures.
- Supervised Learning: How to Predict Customer Churn in a Telecommunications Company : Create a model to predict customer churn in Telecommunications Companies to deal with competition between providers which causes a reduction in company revenue.
- Unsupervised Learning: Clustering Customer Airline Company : Develop clustering models to group customers based on common characteristics, with the aim of providing valuable information for companies in optimizing their business strategies, such as marketing, customer retention, and developing better products and services. By helping companies make more informed and accurate decisions.
- Reinforcement Learning: --- :
- Clothing Reviews Neural Network Model with TensorFlow: Build a neural network model that was developed using the TensorFlow framework, to classify or predict clothing product reviews (clothing reviews).
- Classification of Skin Cancer: Create a skin cancer classification model using Tensorflow. A skin cancer classification model using Tensorflow is being developed to recognize skin images showing signs of skin cancer. Building this model requires an expert team of data scientists, healthcare professionals, and developers to ensure its safety and correctness.
- An Analysis of Stock Prices: This analysis is conducted to see stock price trends, predict future stock prices, or to look for factors that influence stock price movements. In this analysis, time series analysis methods are used. The ultimate goal of this analysis is to provide useful insights for investors in making investment decisions.
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Predict Customer Personality to boost marketing campaign by using Machine Learning: Processes historical marketing campaign data to improve performance and target the right customers to transact on enterprise platforms using Machine Learning. For more Visit on: Article link
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Predict Customer Clicked Ads Classification by Using Machine Learning: Knowing the effectiveness of an advertisement that they display, for companies engaged in digital marketing consulting to find out how much the advertisement has been marketed so that it can attract customers to see the advertisement. For more Visit on: Article link
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Investigate Hotel Business using Data Visualization: Get insights related to hotel business performance. with data exploration, such as analyzing how customers behave in ordering hotel tickets or looking for factors that influence the cancellation of hotel ticket bookings. then the insights obtained are presented using visualization and data storytelling. For more Visit on: Article link
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Improving Employee Retention by Predicting Employee Attrition Using Machine Learning: Explain the conditions of employees and explore the problems that exist within the company that cause the employee to resign so as to reduce the rate of resignation of employees, and can describe a strategy that can increase employee retention. presenting descriptive findings from data using data visualization and data storytelling, and obtaining inferential findings using statistical analysis or machine learning approaches. For more Visit on: Article link