Hi there! I'm Adam Stogsdill (He/Him). I'm a Biotechnical AI/ML Engineer at RAIsonance. Currently interested in joining a PhD program in AI focusing on medical data and diagnostics.
Private Email: [email protected]
Below is a step-by-step path of a mathematical journey that I will take to enhance and solidify my mathematical foundations and help reach profiency in advanced statistical methods.
Step 1: Master the Foundations
- Introduction to Proof Techniques:
- Resources:
- Textbook: "How to Prove It: A Structured Approach" by Daniel J. Velleman
- Online Course: "Introduction to Mathematical Proofs" by Khan Academy
- Resources:
- Discrete Mathematics:
- Resources:
- Textbook: "Discrete Mathematics and Its Applications" by Kenneth H. Rosen
- Online Course: "Discrete Mathematics" by MIT OpenCourseware
- Resources:
- Linear Algebra:
- Resources:
- Textbook: "Linear Algebra Done Right" by Sheldon Axler
- Online Course: "MIT OpenCourseware 18.06: Linear Algebra"
- Resources:
Step 2: Deepen Your Understanding with Core Mathematics
- Calculus I, II, III:
- Resources:
- Textbook: "Calculus: Early Transcendentals" by James Stewart
- Online Course: "Calculus" by Khan Academy
- Resources:
- Real Analysis:
- Resources:
- Textbook: "Principles of Mathematical Analysis" by Walter Rudin
- Online Course: "Real Analysis" by MIT OpenCourseware
- Resources:
- Complex Analysis:
- Resources:
- Textbook: "Complex Analysis" by Lars Ahlfors
- Online Course: "Complex Analysis" by MIT OpenCourseware
- Resources:
- Abstract Algebra:
- Resources:
- Textbook: "Abstract Algebra" by David S. Dummit and Richard M. Foote
- Online Course: "Abstract Algebra" by Stanford University
- Resources:
Step 3: Explore Advanced Topics
- Number Theory:
- Resources:
- Textbook: "Elementary Number Theory" by David M. Burton
- Online Course: "Number Theory" by Khan Academy
- Resources:
- Differential Equations:
- Resources:
- Textbook: "Differential Equations with Applications and Historical Notes" by George F. Simmons
- Online Course: "Differential Equations" by MIT OpenCourseware
- Resources:
- Topology:
- Resources:
- Textbook: "Topology" by James Munkres
- Online Course: "Topology" by Stanford University
- Resources:
- Statistical Learning:
- Resources:
- Textbook: "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
- Online Course: "Machine Learning" by Andrew Ng on Coursera
- Resources:
Step 4: Enhance Your Skills with Specialized Subjects
- Combinatorics:
- Resources:
- Textbook: "A Combinatorial Miscellany" by T. P. McDonough
- Online Course: "Combinatorics" by MIT OpenCourseware
- Resources:
- Optimization:
- Resources:
- Textbook: "Introduction to Linear Optimization" by Dimitris Bertsimas and John N. Tsitsiklis
- Online Course: "Linear Optimization" by MIT OpenCourseware
- Resources:
- Numerical Analysis:
- Resources:
- Textbook: "Numerical Analysis" by Richard L. Burden and J. Douglas Faires
- Online Course: "Numerical Methods for Scientists and Engineers" by edX
- Resources:
- Mathematical Modeling:
- Resources:
- Textbook: "Mathematical Modeling" by J. N. Kapur
- Online Course: "Applied Mathematical Modeling" by Duke University on Coursera
- Resources:
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