A deep dive into machine learning requires a combination of theoretical knowledge and practical skills. Here's a possible learning activity plan:

Learn the fundamentals of machine learning: Before diving deep into machine learning, it's important to have a strong foundation in the basics. Start with learning about the different types of machine learning algorithms, such as supervised, unsupervised, and reinforcement learning. Understand the concepts of training, testing, and validation, and learn about the different performance metrics used to evaluate machine learning models.

Study the math behind machine learning: To truly understand how machine learning algorithms work, you'll need a solid understanding of mathematical concepts such as linear algebra, calculus, and probability theory. Take online courses or read textbooks that cover these subjects in detail.

Gain practical experience: Learning by doing is the best way to gain mastery over machine learning. Work on projects that involve applying machine learning algorithms to real-world datasets. Use tools like Python and its popular machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch to implement the algorithms. Kaggle and GitHub are great resources to find and contribute to open-source machine learning projects.

Attend workshops and conferences: Attend conferences and workshops on machine learning to gain exposure to the latest research and industry practices. Many of these events feature talks, hands-on tutorials, and networking opportunities with experts in the field.

Join online communities: Join online forums and communities such as Reddit's Machine Learning subreddit, Machine Learning Mastery, and KDnuggets to stay up to date on the latest news and trends in machine learning. These communities can also be a great resource for getting help with your projects or answering your questions.

Practice continual learning: Machine learning is a rapidly evolving field, and new techniques and algorithms are developed all the time. Keep up with the latest research by reading academic papers, following blogs and newsletters, and continuing to work on new projects.

Remember, deep diving into machine learning is a continuous process, so be prepared to put in consistent effort to gain mastery over this exciting and constantly evolving field.