avatarNaina Chaturvedi

Summary

The provided content is a comprehensive compilation of coding questions categorized by companies such as Amazon, Dropbox, and Adobe, along with resources for tech interviews, data science and machine learning projects, and system design tutorials.

Abstract

The webpage content serves as a valuable resource for individuals preparing for tech interviews, offering a curated list of coding questions from various tech companies. It includes links to series on topics such as Natural Language Processing (NLP), Data Science, and Machine Learning, complete with projects and videos. The content also highlights the importance of understanding data structures, algorithms, and system design, providing resources for in-depth learning and practice. Additionally, it introduces the reader to a YouTube channel named Ignito, which publishes videos on implemented data science and ML projects, and a newsletter called Tech Brew for ongoing tech insights. The page emphasizes the practical application of knowledge through projects and encourages subscribing to the channel and newsletter for continuous learning.

Opinions

  • The author believes in the importance of practical application and provides numerous project-based resources.
  • There is an emphasis on the value of subscribing to the Ignito YouTube channel and the Tech Brew newsletter for additional learning and staying updated with tech trends.
  • The content suggests that readers should use the provided resources as a reference or practice tool for tech interviews.
  • The author encourages the use of curated lists and mega-compilations for efficient interview preparation.
  • There is a clear opinion that learning should be comprehensive, covering a wide range of topics from coding questions to system design.
  • The inclusion of specific coding problems from companies like Amazon indicates a focus on preparing for interviews at top tech companies.
  • The content conveys that staying informed about the latest tools and techniques in data science and machine learning is crucial for professionals in the field.

Most Popular Coding Questions — Company Wise List : Part 3

Just for your reference…

Pic credits : Unsplash

Welcome back peeps. This post ( part 3 of tech interview series) is for the students who are preparing for their upcoming tech interviews. Use it just as a reference/practice resource.

Some of the other best Series —

30 Days of Natural Language Processing ( NLP) Series

60 days of Data Science and ML Series with projects

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60 Days of Deep Learning with Projects Series

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

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All the Data Science and Machine Learning Resources

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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:

Amazon

Dropbox

Adobe

System Design with Questions

Part 4 :

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 —

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

Software Development
Data Science
Machine Learning
Tech
Programming
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