It’s natural to feel a sense of anxiety and inferiority when comparing your work to experienced professionals on platforms like Kaggle and GitHub. Their exceptional codes, visualizations, and practices utilizing unfamiliar libraries can make your own work seem inadequate. However, it’s important to remember that everyone starts somewhere and learning from these professionals can be a valuable opportunity for growth.

To significantly enhance your coding skills and improve performance, here are some strategies you can consider:

1. Seek Feedback and Mentorship: Actively seek feedback from colleagues, mentors, or online communities dedicated to data science and machine learning. Engaging in code reviews and discussions can help identify areas for improvement and provide valuable insights.
2. Embrace Open-Source Projects: Contribute to open-source projects related to data science and machine learning. This allows you to collaborate with experienced developers and gain exposure to advanced coding techniques and libraries.
3. Practice Reproducible Research: Replicate and implement the codes and visualizations shared by experts in Kaggle competitions or GitHub repositories. This hands-on experience will help you gain a deeper understanding of their approaches and techniques.
4. Participate in Hackathons and Competitions: Engage in data science hackathons and competitions to challenge yourself and learn from others. These events provide a platform to apply new skills, receive feedback, and improve your problem-solving abilities.
5. Continuous Learning: Stay updated with the latest advancements in data science and machine learning. Explore online courses, tutorials, and research papers to broaden your knowledge and keep up with emerging libraries and best practices.
6. Collaborate and Network: Connect with like-minded individuals in the data science community. Collaborate on projects, share ideas, and participate in online forums or local meetups. Networking can expose you to diverse perspectives and provide opportunities for mentorship.

Remember, enhancing coding skills is a gradual process, and it’s important to be patient and persistent. By implementing these strategies and actively seeking improvement, you will gradually overcome your challenges and become a more proficient data scientist.