How I Mastered Data Structures and Algorithms for ML in 6 Weeks
Effective strategies to prepare for coding interviews in machine learning.
1Introduction
A significant portion of coding interviews in machine learning and data science focuses on data structures and algorithms. In this article, I detail the 6-week process I followed to prepare for such interviews.
2Move Away from Traditional Methods
The first step should be to move away from traditional methods of learning data structures and algorithms. This approach requires focusing more on practice than theory.
3Practice-First Learning
Starting to solve problems before learning the topics makes the learning process more effective. This method reinforces theoretical knowledge with practice.
4Daily Routine
Working on two problems every morning for 30-60 minutes over 6 weeks ensures continuous learning. This routine enhances problem-solving skills.
5Understanding Solutions
When solving problems, it's important to understand the model behind the solution, not just the answer. This leads to more effective long-term learning.
6Focus Areas
Focusing on topics frequently asked in machine learning interviews is crucial. These topics include arrays, hash tables, and trees.
7Skipping Advanced Topics
Instead of learning advanced topics like dynamic programming and bit manipulation, focusing on more frequently asked basic topics makes better use of time.
8Conclusion
This approach transformed my understanding of data structures and algorithms and significantly increased my success rate in coding interviews.
Original article: Towards Data Science — 6 Haftada Veri Yapıları ve Algoritmaları Nasıl Öğrendim?