153 Blog Posts To Learn About Mathematics

2026-05-11 · Source: HackerNoon · Field: Science & Research — Mathematics & Computational Sciences, Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, extended

Summary

HackerNoon has compiled 153 free blog posts on mathematics, ordered by reader engagement, available through the Learn Repo. This collection covers a wide array of topics, from fundamental algorithms like Kadane's and Manacher's for maximum subarray sum and longest palindromic substring, to advanced concepts in machine learning and cryptography. Specific articles delve into calculating square roots using the Newton-Raphson method, implementing the Collatz Conjecture in Python, and understanding Two's Complement for binary numbers. The compilation also explores the mathematics behind neural networks, Uniswap formulas, zero-knowledge proofs, and advanced financial risk modeling using hyperbolic graph clustering. It further includes practical applications such as Java programs for geometric checks and multiplication tables, and discussions on the philosophical aspects of mathematics and AI's role in solving complex equations.

Key takeaway

For software engineers and machine learning practitioners seeking to deepen their foundational knowledge, exploring these mathematics-focused articles can significantly enhance problem-solving skills and architectural understanding. You should review topics like algorithmic complexity, cryptographic principles, and the mathematical underpinnings of neural networks to build more robust and efficient systems. Understanding these core concepts will enable you to better optimize code, design secure protocols, and fine-tune AI models.

Key insights

Mathematics underpins diverse technical fields, from algorithms and cryptography to machine learning and finance.

Principles

• Algorithms optimize problem-solving efficiency.
• Mathematical models clarify complex systems.
• Cryptography relies on number theory principles.

Method

The collection highlights methods like Kadane's Algorithm for maximum subarray sum, Newton-Raphson for square roots, and Manacher's Algorithm for longest palindromic substrings, alongside various cryptographic and machine learning techniques.

In practice

• Implement Kadane's for array sum optimization.
• Apply Newton-Raphson for numerical approximations.
• Utilize Two's Complement in binary computations.

Topics

• Algorithms & Data Structures
• Machine Learning Mathematics
• Cryptography & Zero-Knowledge Proofs
• Quantitative Finance
• Programming & Computation

Code references

• hackernoon/learn

Best for: AI Student, Software Engineer, Machine Learning Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by HackerNoon.