avatarNaina Chaturvedi

Summary

The web content provides a comprehensive list of coding questions from various tech companies, along with resources for tech interviews, system design tutorials, and Python project compilations.

Abstract

The website article is a treasure trove for individuals preparing for tech interviews, offering an extensive catalog of coding questions categorized by companies such as Tesla, Twitter, Salesforce, Palantir, Snapchat, Nvidia, Paypal, Two Sigma, and others. It also promotes a YouTube channel, Ignito, which publishes videos on project implementations and coding exercises. Additionally, the article features a tech newsletter for interview tips and techniques, and it links to a series of system design tutorials and Python project compilations, encouraging readers to connect the dots in their learning journey. The content emphasizes the importance of practical implementation through projects and provides resources for a wide range of topics including data science, machine learning, and software development.

Opinions

  • The author believes in the practical approach to learning, emphasizing the importance of project-based implementation.
  • There is a clear endorsement of the Ignito YouTube channel as a valuable resource for visual learners and those who benefit from video tutorials.
  • The author suggests that readers should subscribe to the tech newsletter for continuous learning and updates on the tech industry.
  • The compilation of system design series parts indicates a didactic approach, aiming to guide readers through complex system design concepts in a structured manner.
  • The mention of complete Python and projects mega-compilation suggests that the author values comprehensive learning resources that cover both theory and practice.
  • The article encourages readers to stay tuned for upcoming content, indicating an ongoing commitment to providing educational resources.
  • The author's inclusion of specific coding questions for each company implies that tailoring one's preparation to the company of interest is a strategic approach to tech interviews.

Most Popular Coding Questions — Company Wise List : Part 6

Just for your reference…

Pic credits : Programming Memes

Welcome back peeps. This post ( part 6 of tech interview series) is for the students who are preparing for their upcoming 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.

Projects Videos —

All the projects, data structures, SQL, algorithms, system design, Data Science and ML , Data Analytics, Data Engineering, , Implemented Data Science and ML projects, Implemented Data Engineering Projects, Implemented Deep Learning Projects, Implemented Machine Learning Ops Projects, Implemented Time Series Analysis and Forecasting Projects, Implemented Applied Machine Learning Projects, Implemented Tensorflow and Keras Projects, Implemented PyTorch Projects, Implemented Scikit Learn Projects, Implemented Big Data Projects, Implemented Cloud Machine Learning Projects, Implemented Neural Networks Projects, Implemented OpenCV Projects,Complete ML Research Papers Summarized, Implemented Data Analytics projects, Implemented Data Visualization Projects, Implemented Data Mining Projects, Implemented Natural Leaning Processing Projects, MLOps and Deep Learning, Applied Machine Learning with Projects Series, PyTorch with Projects Series, Tensorflow and Keras with Projects Series, Scikit Learn Series with Projects, Time Series Analysis and Forecasting with Projects Series, ML System Design Case Studies Series videos will be published on our youtube channel ( just launched).

Subscribe today!

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 :

Part 1 of this series -

Part2:

Part 3:

Part 4 :

Part 5 :

Tesla

Twitter

Salesforce

Palantir

Samsung

Snapchat

Nvidia

Paypal

Two Sigma

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 —

Part 7: Coming soon!

Stay Tuned!

For Python Projects —

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

Follow for more updates. Stay tuned and keep coding!

For other projects, tune to —

Build Machine Learning Pipelines( With Code)

Recurrent Neural Network with Keras

Clustering Geolocation Data in Python using DBSCAN and K-Means

Facial Expression Recognition using Keras

Hyperparameter Tuning with Keras Tuner

Custom Layers in Keras

Programming
Tech
Machine Learning
Data Science
Software Development
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