ok, sounds good, now that i look at it it does seem a bit weird
10 karma · joined December 11, 2023
1) Emphasize completing courses/books before 11th grade.
2) Focus on projects rather than numerous courses.
3) Watch 3blue1brown's series on linear algebra, calculus, and deep learning.
4) Recommended resources include Free Code Camp, CS50, How to Design Programs, and Nand2Tetris.
5) Stress the importance of mathematics in AI/ML and suggest studying probability, calculus, and linear algebra.
6) Encourage the individual to start with simple projects and gradually tackle more ambitious ones.
7) Suggest writing a complete, original application with documentation to understand code organization.
8) Advise joining projects, looking for internships, and exploring open-source contributions.
9) Recommend Francois Chollet's book on AI and learning TensorFlow and Keras.
10)Encourage learning practical aspects of ML/AI, such as data partitioning and avoiding overfitting.
11)Suggest building something personally interesting or cloning an existing project.
12)Emphasize the importance of soft skills and understanding the human side of technology.