Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

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🔖 Cheat sheets on Transformers and LLMs from Stanford

We found an excellent set of materials from the Stanford CME-295 course on large language models.

They cover tokenization, the self-attention mechanism, prompting, fine-tuning, LLM-as-a-judge, RAG, AI agents, and reasoning models.

⛓️ Download here
https://github.com/afshinea/stanford-cme-295-transformers-large-language-models
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On Reddit, someone collected all the resources they used to prepare for interviews on algorithms, system design, and machine coding. In the end, they made it to a Google interview.

1. Algorithms and Patterns

Before grinding on problems, it's worth understanding the patterns.

• All LeetCode Articles on Coding Patterns Summarized
https://leetcode.com/discuss/interview-question/5366542/all-leetcode-articles-on-coding-patterns-summarized-in-one-page

• Solved All Two Pointers Problems in 100 Days
https://leetcode.com/discuss/study-guide/1688903/Solved-all-two-pointers-problems-in-100-days

• Tree Question Pattern 2023 — Tree Study Guide
https://leetcode.com/discuss/study-guide/2879240/tree-question-pattern-2023-tree-study-guide

• Important and Useful Links from All Over LeetCode
https://leetcode.com/discuss/general-discussion/665604/Important-and-Useful-links-from-all-over-the-LeetCode

• Coding Interview Preparation Problems for Beginners
https://leetcode.com/discuss/interview-question/448284/Coding-Interview-preparation-problems-for-beginners

2. Preparation for Companies

• Google, Meta, Apple, Amazon Senior SDE Preparation
https://prachub.com/?sort=hot&company=Meta%2CGoogle%2CTikTok%2CAmazon

• A Study Guide for Passing the Google Interview
https://prachub.com/interview-guide

The author also made a small tracker for preparation:

• company-specific questions
• Todo / Solved / Revision statuses
• automatic repetition scheduling
• AI assistant with hints instead of ready-made solutions

https://prachub.com/questions

3. System Design (HLD)

Instead of random articles — structured collections:

• Arch 25 — the most common systems and patterns
• Arch 50 — infrastructure, data, and fault tolerance
• Arch 75 — more complex scenarios and company-specific specialization
• Arch All — a full bank of 103 HLD tasks
• Core Concepts — 33 breakdowns of distributed systems

4. Machine Coding / LLD

Many underestimate this part until their first interview failure.

• MaCo 30 — the most common tasks
• MaCo 60 — an extended collection
• MaCo All — a full set of 103 tasks
• Design Patterns — 31 design patterns
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