I feel so behind, Where do I start

1. 1Review your existing knowledge of models like GLM, LR, XGBoost, and Random Forest to identify areas for improvement
2. 2Explore and apply more advanced models like neural networks and deep learning techniques
3. 3Build projects that integrate multiple models and techniques to solve real-world problems
4. 4Configure and test your models using Kaggle and other platforms to evaluate performance
5. 5Apply your skills to different domains and datasets to deepen your understanding

Data scientists and analysts on a team can benefit from this approach to upskill and tackle more complex projects, and having a clear plan helps them contribute more effectively to the team's goals

💡 Having a clear roadmap and building on existing knowledge is key to advancing in machine learning

🚀 Boost your ML skills by building on what you know and creating a roadmap for deeper learning! 💡