avatarNaina Chaturvedi

Summary

The webpage provides a comprehensive guide to popular coding interview questions, focusing on backtracking, binary search, trees, and other algorithms, along with system design topics, through a curated list of resources, articles, and projects.

Abstract

The website serves as a valuable resource for individuals preparing for technical interviews in the field of software engineering. It compiles an extensive list of frequently asked coding questions, particularly emphasizing backtracking, binary search, and tree-related problems. These questions are sourced from platforms like LeetCode and are accompanied by links to detailed articles and tutorials. The guide also includes a series of system design topics, presented in a multi-part format, which covers essential concepts and practical applications. Additionally, the website offers insights into Python programming, data science, machine learning projects, and provides access to a tech newsletter for ongoing learning and updates in the tech industry.

Opinions

  • The author emphasizes the importance of practice and reference for tech interview preparation, suggesting that the provided list is essential for candidates aiming to crack technical interviews.
  • There is an underlying belief that a structured approach to learning, as presented in the series of articles, is beneficial for grasping complex topics in system design and algorithms.
  • The inclusion of projects and practical examples indicates a pedagogical approach that values hands-on experience as a critical component of the learning process.
  • The author advocates for continuous learning and engagement within the tech community, as evidenced by the invitation to subscribe to a tech newsletter for the latest insights and tips.
  • By providing a diverse range of topics, from advanced Python concepts to data preprocessing and visualization, the author suggests that a well-rounded knowledge base is crucial for success in the tech field.
  • The frequent use of motivational quotes and phrases like "Connect the dots" and "Ignito" reflects an encouraging and motivational tone, aiming to inspire readers in their learning journey.

The Most Popular Backtracking, Binary Search, Trees Questions

Just for reference…

Pic credits : github

Welcome back peeps. This post is for the students who are preparing for their tech interviews. While I’m sitting on the other side of the table as an interviewer now; I know how daunting the prep journey can be. Use it just as a reference/practice resource.

All the Complete System Design Series Parts —

1. System design basics

2. Horizontal and vertical scaling

3. Load balancing and Message queues

4. High level design and low level design, Consistent Hashing, Monolithic and Microservices architecture

5. Caching, Indexing, Proxies

6. Networking, How Browsers work, Content Network Delivery ( CDN)

7. Database Sharding, CAP Theorem, Database schema Design

8. Concurrency, API, Components + OOP + Abstraction

9. Estimation and Planning, Performance

10. Map Reduce, Patterns and Microservices

11. SQL vs NoSQL and Cloud

12. Most Popular System Design Questions

Github —

Backtracking

Curated List — The Top & Most Frequently Asked Coding Questions You Should Practice

Most Popular Coding Questions — Company Wise List : Part 1

System Design

Most Popular Coding Questions — Company Wise List : Part 2

Binary Search

Interval

Python Iterators, Generators And Decorators Made Easy

Tree

Complete Data Preprocessing and Data Visualization with Projects — Mega Compilation Part 2

Python projects —

Two pointers

Day 1 — Day 60 : Quick Recap of 60 days of Data Science and ML

Fast & Slow pointers

Part 2 of Data Science and ML mega series ( Day 21 — Day 35) can be found here —

More Coming Soon!

Some of the other best Series —

30 Days of Natural Language Processing ( NLP) Series

30 days of Data Engineering with projects Series

60 days of Data Science and ML Series with projects

100 days : Your Data Science and Machine Learning Degree Series with projects

23 Data Science Techniques You Should Know

Tech Interview Series — Curated List of coding questions

Complete System Design with most popular Questions Series

Complete Data Visualization and Pre-processing Series with projects

Complete Python Series with Projects

Complete Advanced Python Series with Projects

Kaggle Best Notebooks that will teach you the most

Complete Developers Guide to Git

All the Data Science and Machine Learning Resources

210 Machine Learning Projects

30 days of Machine Learning Ops

Tech Newsletter —

If you are interested, you can join my newsletter through which I send tech interview tips, techniques, patterns, hacks — Software Development, ML, Data Science, Startups and Technology projects to more than 30K readers. You can subscribe to Tech Brew :

More Projects —

Complete Python And Projects — Mega Compilation

Complete Data Preprocessing and Data Visualization with Projects — Mega Compilation Part 2

Maths —

Statistics for Data Science and Machine Learning with Code Implementation

Maths for Data Science and Machine learning

In this post we covered Maths for ML . Topics like Linear Algebra, Calculus, Matrix and Vectors, Bayes Theorem and Cheatsheets etc are covered in detail.

For other projects, tune to —

Build Machine Learning Pipelines( With Code)

Recurrent Neural Network with Keras

Custom Layers in Keras

Follow for more updates, stay tuned and of-course let me end this post with a quote by Steve Jobs ;)

“Your time is limited, so don’t waste it living someone else’s life.”

Tech
Programming
Software Development
Data Science
Machine Learning
Recommended from ReadMedium