Data Science Machine Learning Data Analysis
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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
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๐—ฌ๐—ผ๐˜‚๐—ฟ_๐——๐—ฎ๐˜๐—ฎ_๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ_๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„_๐—ฆ๐˜๐˜‚๐—ฑ๐˜†_๐—ฃ๐—น๐—ฎ๐—ป.pdf
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1. Master the fundamentals of Statistics

Understand probability, distributions, and hypothesis testing

Differentiate between descriptive vs inferential statistics

Learn various sampling techniques

2. Get hands-on with Python & SQL

Work with data structures, pandas, numpy, and matplotlib

Practice writing optimized SQL queries

Master joins, filters, groupings, and window functions

3. Build real-world projects

Construct end-to-end data pipelines

Develop predictive models with machine learning

Create business-focused dashboards

4. Practice case study interviews

Learn to break down ambiguous business problems

Ask clarifying questions to gather requirements

Think aloud and structure your answers logically

5. Mock interviews with feedback

Use platforms like Pramp or connect with peers

Record and review your answers for improvement

Gather feedback on your explanation and presence

6. Revise machine learning concepts

Understand supervised vs unsupervised learning

Grasp overfitting, underfitting, and bias-variance tradeoff

Know how to evaluate models (precision, recall, F1-score, AUC, etc.)

7. Brush up on system design (if applicable)

Learn how to design scalable data pipelines

Compare real-time vs batch processing

Familiarize with tools: Apache Spark, Kafka, Airflow

8. Strengthen storytelling with data

Apply the STAR method in behavioral questions

Simplify complex technical topics

Emphasize business impact and insight-driven decisions

9. Customize your resume and portfolio

Tailor your resume for each job role

Include links to projects or GitHub profiles

Match your skills to job descriptions

10. Stay consistent and track progress

Set clear weekly goals

Monitor covered topics and completed tasks

Reflect regularly and adapt your plan as needed


#DataScience #InterviewPrep #MLInterviews #DataEngineering #SQL #Python #Statistics #MachineLearning #DataStorytelling #SystemDesign #CareerGrowth #DataScienceRoadmap #PortfolioBuilding #MockInterviews #JobHuntingTips


โœ‰๏ธ Our Telegram channels: https://t.iss.one/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ_๐——๐—ฒ๐˜€๐—ถ๐—ด๐—ป_๐—ฅ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ_๐—ณ๐—ผ๐—ฟ_๐— ๐—”๐—”๐—ก๐—š_&_๐—•๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ.pdf
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๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ ๐——๐—ฒ๐˜€๐—ถ๐—ด๐—ป ๐—ฅ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ ๐—ณ๐—ผ๐—ฟ ๐— ๐—”๐—”๐—ก๐—š & ๐—•๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ ๐Ÿš€
If you're targeting top product companies or leveling up your backend/system design skills, this is for you.

System Design is no longer optional in tech interviews. Itโ€™s a must-have.
From Netflix, Amazon, Uber, YouTube, Reddit, Inc., to Twitter, these case studies and topic breakdowns will help you build real-world architectural thinking.

๐Ÿ“Œ Save this post. Spend 40 mins/day. Stay consistent.


โžŠ ๐— ๐˜‚๐˜€๐˜-๐—ž๐—ป๐—ผ๐˜„ ๐—–๐—ผ๐—ฟ๐—ฒ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€

๐Ÿ‘‰ System Design Basics
๐Ÿ”— https://bit.ly/3SuUR0Y)

๐Ÿ‘‰ Horizontal & Vertical Scaling
๐Ÿ”— https://bit.ly/3slq5xh)

๐Ÿ‘‰ Load Balancing & Message Queues
๐Ÿ”— https://bit.ly/3sp0FP4)

๐Ÿ‘‰ HLD vs LLD, Hashing, Monolith vs Microservices
๐Ÿ”— https://bit.ly/3DnEfEm)

๐Ÿ‘‰ Caching, Indexing, Proxies
๐Ÿ”— https://bit.ly/3SvyVDc)

๐Ÿ‘‰ Networking, CDN, How Browsers Work
๐Ÿ”— https://bit.ly/3TOHQRb

๐Ÿ‘‰ DB Sharding, CAP Theorem, Schema Design
๐Ÿ”— https://bit.ly/3CZtfLN

๐Ÿ‘‰ Concurrency, OOP, API Layering
๐Ÿ”— https://bit.ly/3sqQrhj

๐Ÿ‘‰ Estimation, Performance Optimization
๐Ÿ”— https://bit.ly/3z9dSPN

๐Ÿ‘‰ MapReduce, Design Patterns
๐Ÿ”— https://bit.ly/3zcsfmv

๐Ÿ‘‰ SQL vs NoSQL, Cloud Architecture
๐Ÿ”— https://bit.ly/3z8Aa49)


โž‹ ๐— ๐—ผ๐˜€๐˜ ๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ ๐——๐—ฒ๐˜€๐—ถ๐—ด๐—ป ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€

๐Ÿ”— https://bit.ly/3Dp40Ux
๐Ÿ”— https://bit.ly/3E9oH7K


โžŒ ๐—–๐—ฎ๐˜€๐—ฒ ๐—ฆ๐˜๐˜‚๐—ฑ๐˜† ๐——๐—ฒ๐—ฒ๐—ฝ ๐——๐—ถ๐˜ƒ๐—ฒ๐˜€ (๐—ฃ๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐—ฐ๐—ฒ ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ!)

๐Ÿ‘‰ Design Netflix
๐Ÿ”— https://bit.ly/3GrAUG1

๐Ÿ‘‰ Design Reddit
๐Ÿ”— https://bit.ly/3OgGJrL

๐Ÿ‘‰ Design Messenger
๐Ÿ”— https://bit.ly/3DoAAXi

๐Ÿ‘‰ Design Instagram
๐Ÿ”— https://bit.ly/3BFeHlh

๐Ÿ‘‰ Design Dropbox
๐Ÿ”— https://bit.ly/3SnhncU

๐Ÿ‘‰ Design YouTube
๐Ÿ”— https://bit.ly/3dFyvvy

๐Ÿ‘‰ Design Tinder
๐Ÿ”— https://bit.ly/3Mcyj3X

๐Ÿ‘‰ Design Yelp
๐Ÿ”— https://bit.ly/3E7IgO5

๐Ÿ‘‰ Design WhatsApp
๐Ÿ”— https://bit.ly/3M2GOhP

๐Ÿ‘‰ Design URL Shortener
๐Ÿ”— https://bit.ly/3xP078x

๐Ÿ‘‰ Design Amazon Prime Video
๐Ÿ”—https://bit.ly/3hVpWP4

๐Ÿ‘‰ Design Twitter
๐Ÿ”— https://bit.ly/3qIG9Ih

๐Ÿ‘‰ Design Uber
๐Ÿ”— https://bit.ly/3fyvnlT

๐Ÿ‘‰ Design TikTok
๐Ÿ”— https://bit.ly/3UUlKxP

๐Ÿ‘‰ Design Facebook Newsfeed
๐Ÿ”— https://bit.ly/3RldaW7

๐Ÿ‘‰ Design Web Crawler
๐Ÿ”— https://bit.ly/3DPZTBB

๐Ÿ‘‰ Design API Rate Limiter
๐Ÿ”— https://bit.ly/3BIVuh7


โž ๐—™๐—ถ๐—ป๐—ฎ๐—น ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ ๐——๐—ฒ๐˜€๐—ถ๐—ด๐—ป ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ๐˜€

๐Ÿ‘‰ All Solved Case Studies
๐Ÿ”— https://bit.ly/3dCG1rc

๐Ÿ‘‰ Design Terms & Terminology
๐Ÿ”— https://bit.ly/3Om9d3H

๐Ÿ‘‰ Complete Basics Series
๐Ÿ”—https://bit.ly/3rG1cfr

#SystemDesign #TechInterviews #MAANGPrep #BackendEngineering #ScalableSystems #HLD #LLD #SoftwareArchitecture #DesignCaseStudies #CloudArchitecture #DataEngineering #DesignPatterns #LoadBalancing #Microservices #DistributedSystems


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๐Ÿ“Œ How to Crack Machine Learning System-Design Interviews

๐Ÿ—‚ Category: MACHINE LEARNING

๐Ÿ•’ Date: 2025-11-14 | โฑ๏ธ Read time: 15 min read

Ace your machine learning system design interviews at top tech companies. This comprehensive guide provides a deep dive into the interview process at Meta, Apple, Reddit, Amazon, Google, and Snap, equipping you with the strategies needed to succeed in these high-stakes technical assessments.

#MachineLearning #SystemDesign #TechInterview #AI