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In this project, data analytics is used to analyze customer-level data of a leading telecom firm, build predictive models to identify customers at high risk of churn, and identify the main indicators of churn. The project focuses on a four-month window, wherein the first two months are the ‘good’ phase, the third month is the ‘action’ phase, while the fourth month is the ‘churn’ phase. The business objective is to predict the churn in the last i.e. fourth month using the data from the first three months.

License: MIT License

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telecom-churn-prediction's Introduction

Hi 👋🏼, I am Chaitanya Chaudhari!

Welcome to my GitHub profile 🙏🏼

About Me:

Machine Learning Engineer | Data Scientist

An enthusiastic and seasoned professional leveraging the power of data and machine learning to resolve intricate problems.

🔭 Innovating: Unleashing data alchemy as a Data Maverick.

🌱 Absorbing: Soaking up the latest data sorcery for transformative insights.

💬 Contemplating: Exploring the enigmatic realm of data's hidden symphony.

📧 Reach Out: Contact me via email at [email protected].

⚡ Zephyr-chaser: Pursuing diverse data realms with a whimsical flair!

Profile Summary

As a passionate machine learning engineer and data scientist, I am driven by the potential of technology to address complex challenges. With a strong background in statistics, machine learning, artificial intelligence, computer vision, deep learning, mathematics, and NLP, I am constantly improving my skills and deepening my understanding in these areas. I place a strong emphasis on delivering quality outcomes while recognizing the importance of continuous learning and growth.

With a focus on data science and machine learning, I am committed to making a positive difference. My portfolio, featuring my work and contributions, can be viewed on GitHub (here, under repositories) and Tableau. I am grateful for opportunities to grow as a professional and showcase my expertise and commitment to making a lasting impact. If you share my vision and wish to collaborate, feel free to reach out at 📫 [email protected]