https://github.com/junfanz1/Awesome-AI-Engineer-Review
Taking notes on Quant Finance, Machine Learning, Computer Science
https://github.com/junfanz1/Awesome-AI-Engineer-Review
List: Awesome-AI-Engineer-Review
Last synced: 3 months ago
JSON representation
Taking notes on Quant Finance, Machine Learning, Computer Science
- Host: GitHub
- URL: https://github.com/junfanz1/Awesome-AI-Engineer-Review
- Owner: junfanz1
- Created: 2021-04-14T16:33:08.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-12-17T15:39:41.000Z (about 1 year ago)
- Last Synced: 2024-12-17T16:36:12.173Z (about 1 year ago)
- Homepage:
- Size: 5.88 MB
- Stars: 44
- Watchers: 1
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - Awesome-AI-Engineer-Review - In-depth review of industry trends in AI, LLMs, Machine Learning, Computer Science, and Quantitative Finance. . (Other Lists / TeX Lists)
README
Views:
•
Followers:
•
Stars:
# Awesome AI Engineer Review
In-depth review of industry trends in AI, LLMs, Machine Learning, Computer Science, and Quantitative Finance.
- [__2025 NVIDIA GTC Conference − Technical & Industrial Insight__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/NVIDIA%20GTC/GTC%202025.md) 
- [__2025 Agentic AI Summit Berkeley − Technical & Industrial Insight__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Agentic%20AI%20Summit/Agentic%20AI%20Summit%20Berkeley%202025.md) 
- [1. NVIDIA GTC | AI Conference for Developers](#1-nvidia-gtc-ai-conference-for-developers)
- [2. Agentic AI Summit](#2-agentic-ai-summit)
- [3. LLM Essentials](#3-llm-essentials)
* [LLM Theory](#llm-theory)
* [LLM Applications](#llm-applications)
* [RAG](#rag)
* [Multi-Agent](#multi-agent)
- [4. DeepSeek & Kimi ](#4-deepseek-kimi)
* [Research Implementation](#research-implementation)
* [DeepSeek Theory](#deepseek-theory)
* [DeepSeek Applications](#deepseek-applications)
* [Kimi K2](#kimi-k2)
- [5. 2025 Paper Reading](#5-2025-paper-reading)
* [Jason Wei: 3 Ideas to Understand AI in 2025](#jason-wei-3-ideas-to-understand-ai-in-2025)
* [World Model: 5 Debates Between Eric Xing's PAN & Yann LeCun’s JEPA](#world-model-5-debates-between-eric-xings-pan-yann-lecuns-jepa)
* [30 Takeaways from Shunyu Yao's Talk on Agentic AI](#30-takeaways-from-shunyu-yaos-talk-on-agentic-ai)
* [Building Web Agents](#building-web-agents)
* [Future of AI Agents = Agentic RL + Pretraining?](#future-of-ai-agents-agentic-rl-pretraining)
* [HiVA: Self-organized Hierarchical Variable Agent via Goal-driven Semantic-Topological Evolution](#hiva-self-organized-hierarchical-variable-agent-via-goal-driven-semantic-topological-evolution)
- [6. LangGraph & Cursor AI Projects](#6-langgraph-cursor-ai-projects)
- [7. System Design](#7-system-design)
* [ByteByteGo - GenAI/ML/Modern System Design Interview](#bytebytego-genaimlmodern-system-design-interview)
* [Educative - GenAI/Modern System Design Interview](#educative-genaimodern-system-design-interview)
- [8. Computer Systems](#8-computer-systems)
- [9. Big Data and AI in Finance, Econometrics and Statistics Conference, UChicago 2024](#9-big-data-and-ai-in-finance-econometrics-and-statistics-conference-uchicago-2024)
- [10. C++ Design Patterns and Derivatives Pricing](#10-c-design-patterns-and-derivatives-pricing)
- [11. High-Frequency Finance](#11-high-frequency-finance)
- [12. Machine Learning for Algorithmic Trading](#12-machine-learning-for-algorithmic-trading)
- [13. Stochastic Volatility Modeling](#13-stochastic-volatility-modeling)
- [14. Quant Job Interview Questions](#14-quant-job-interview-questions)
* [Star History](#star-history)
---
# 1. NVIDIA GTC | AI Conference for Developers
> [__2025 NVIDIA GTC Conference − Technical & Industrial Insight__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/NVIDIA%20GTC/GTC%202025.md)
> [__GTC 2024 Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/NVIDIA%20GTC/GTC%202024.md)
> [__2025 Agentic AI Summit Berkeley − Technical & Industrial Insight__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Agentic%20AI%20Summit/Agentic%20AI%20Summit%20Berkeley%202025.md)
Dive into DeepSeek LLM, by Xiaojing Ding, 2025
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/Dive%20into%20DeepSeek%20LLM.md)
DeepSeek Large Model High-Performance Core Technology and Multimodal Fusion Development, by Xiaohua Wang, 2025
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/DeepSeek%20Large%20Model.md)
Efficient Training in PyTorch, by Ailing Zhang, 2024
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/Efficient%20Training%20PyTorch.md)
---
Generative AI on AWS, by Chris Fregly, 2024
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/Generative%20AI%20on%20AWS.md)
LLM from Theory to Practice, by Qi Zhang, 2024
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/LLM%20from%20Theory%20to%20Practice.md)
LangChain Scalable LLM Apps, by Teli Li, 2024
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/LangChain%20Scalable%20LLM%20Apps.md)
---
Foundations of LLMs - by Yuren Mao, Zhejiang University, 2024
> [Course Github](https://github.com/ZJU-LLMs/Foundations-of-LLMs) | [Course Video](https://www.bilibili.com/video/BV1PB6XYFET2) | [Textbook](https://github.com/ZJU-LLMs/Foundations-of-LLMs/blob/main/%E3%80%8A%E5%A4%A7%E6%A8%A1%E5%9E%8B%E5%9F%BA%E7%A1%80%E3%80%8B%E6%95%99%E6%9D%90/%E5%A4%A7%E6%A8%A1%E5%9E%8B%E5%9F%BA%E7%A1%80%20%E5%AE%8C%E6%95%B4%E7%89%88.pdf) | [__PDF Notes-Chinese__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/Foundations%20of%20LLMs/%E6%B5%99%E5%A4%A7%E5%A4%A7%E6%A8%A1%E5%9E%8B%E8%AF%BE%E7%AC%94%E8%AE%B0.pdf)
30 Essential Questions and Answers on Machine Learning and AI - by Sebastian Raschka, 2025
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/30%20ML%20AI.md)
Unveiling Large Model, by Liang Wen, 2025
> [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Foundations%20of%20LLMs/Unveiling%20Large%20Model.md)
---
> [GeekBang: AI LLM Practice](https://time.geekbang.org/column/intro/100770601) | [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/AI%20LLM/AI%20LLM%20Practice.md)
> [GeekBang: AI LLM System](https://time.geekbang.org/column/article/852628) | [__Notes-Chinese__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/AI%20LLM/AI%20System.md)
> [GeekBang: AI LLM Project Implementation](https://time.geekbang.org/column/article/801454) | [__Notes-Chinese__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/AI%20LLM/LLM%20Project.md)
> [GeekBang: LLM App Developmenmt](https://time.geekbang.org/column/intro/100764201) | [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/AI%20LLM/LLM%20App.md)
> [Educative: Advanced RAG Techniques - Choosing the Right Approach](https://www.educative.io/verify-certificate/pg03nJFvpmPgN4W0Zuxy07pVPro3h2) | [__Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/AI%20LLM/Advanced%20RAG.md)
> [GeekBang: RAG Development](https://time.geekbang.org/column/intro/100804101?tab=catalog) | [__Notes-Chinese__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/edit/main/AI%20LLM/RAG.md)
> [Educative: Build AI Agents and Multi-Agent Systems with CrewAI](https://www.educative.io/verify-certificate/k5m3gACoj1xDYoOq7c0Kjk4y2AoGTn) | [__Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/AI%20LLM/CrewAI.md)
> [GeekBang: AI Agents](https://time.geekbang.org/course/intro/100775901?tab=catalog) | [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/AI%20LLM/AI%20Agent.md)
> [Github: Mixture-of-Experts (MoE) Implementation in PyTorch](https://github.com/junfanz1/MoE-Mixture-of-Experts)
> [Github: MiniGPT-and-DeepSeek-MLA-Multi-Head-Latent-Attention](https://github.com/junfanz1/DeepSeek-MLA)
> [Educative: Everything You Need to Know About DeepSeek](https://www.educative.io/verify-certificate/GZjlABCqZ1G2n7mWjuroy1MXK2GBIm) | [__Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/DeepSeek/DeepSeek%20Essentials.md)
> [Zomi-Bilibili](https://space.bilibili.com/517221395/upload/video) | [Github](https://github.com/chenzomi12/AIFoundation/) | [__Notes-Chinese__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/DeepSeek/DeepSeek%20Theory.md)
> [GeekBang: DeepSeek HandsOn](https://time.geekbang.org/column/101000501) | [__Notes-Chinese__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/DeepSeek/DeepSeek%20HandsOn.md)
> [GeekBang: DeepSeek App Development](https://time.geekbang.org/column/intro/100995901) | [__Notes-Chinese__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/DeepSeek/DeepSeek%20Developer%20Practice.md)
> [Kimi K2](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/DeepSeek/Kimi%20K2.md) | [🚀 Understand Kimi K2 in 10 Minutes](https://www.linkedin.com/pulse/understand-kimi-k2-10-minutes-jf-ai-vnsqc/)
## Jason Wei: 3 Ideas to Understand AI in 2025
> [Jason Wei: 3 Ideas to Understand AI in 2025](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Paper%20Reading/Jason%20Wei%3A%203%20Ideas%20to%20Understand%20AI%20in%202025.md) | [LinkedIn: Jason Wei: 3 Ideas to Understand AI in 2025](https://www.linkedin.com/pulse/06-jason-weis-3-ideas-understand-ai-2025-jf-ai-v7rgc/)
## World Model: 5 Debates Between Eric Xing's PAN & Yann LeCun’s JEPA
> [World Models](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Paper%20Reading/World%20Models.md) | [LinkedIn: World Model: 5 Debates Between Eric Xing's PAN & Yann LeCun’s JEPA](https://www.linkedin.com/pulse/world-model-5-debates-between-eric-xings-pan-yann-lecuns-jepa-jf-ai-8xigc/)
## 30 Takeaways from Shunyu Yao's Talk on Agentic AI
> [Shunyu Yao on Agentic AI](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Paper%20Reading/Shunyu%20Yao%20Agentic%20AI.md) | [LinkedIn: 30 Takeaways from Shunyu Yao's Talk on Agentic AI](https://www.linkedin.com/pulse/30-takeaways-from-shunyu-yaos-talk-agentic-ai-jf-ai-dqz6c)
> [Building Web Agents](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Paper%20Reading/Building%20Web%20Agents.md) | [LinkedIn: Building Web Agents](https://www.linkedin.com/pulse/building-web-agents-jf-ai-khjic)
## Future of AI Agents = Agentic RL + Pretraining?
> [Future of AI Agents = Agentic RL + Pretraining?](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Paper%20Reading/Future%20of%20AI%20Agents%20%3D%20Agentic%20RL%20%2B%20Pretraining%3F.md) | [LinkedIn: Future of AI Agents = Agentic RL + Pretraining?](https://www.linkedin.com/pulse/future-ai-agents-agentic-rl-pretraining-jf-ai-p0nlc/)
## HiVA: Self-organized Hierarchical Variable Agent via Goal-driven Semantic-Topological Evolution
> [HiVA: Self-organized Hierarchical Variable Agent via Goal-driven Semantic-Topological Evolution](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/Paper%20Reading/HiVA:%20Self-organized%20Hierarchical%20Variable%20Agent%20via%20Goal-driven%20Semantic-Topological%20Evolution.md) | [LinkedIn: Co-Evolutionary Path Towards Organizational Intelligence: How Structure-as-Memory Network & Multi-Agent Emergence Could Unlock AGI?](https://www.linkedin.com/pulse/07-co-evolutionary-path-towards-organizational-intelligence-how-kpqjc/)
# 6. LangGraph & Cursor AI Projects
> [__Notes__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/LangChain/Projects.md)
- [Ed Donner: LLM Engineering: Master AI, Large Language Models & Agents](https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models)
- [Eden Marco: LangChain-Develop LLM powered applications with LangChain](https://www.udemy.com/course/langchain/)
- [Eden Marco: LangGraph-Develop LLM powered AI agents with LangGraph](https://www.udemy.com/course/langgraph)
- [Eden Marco: Cursor Course: FullStack development with Cursor AI Copilot](https://www.udemy.com/course/cursor-ai-ide/)
> GitHub Projects
- [MCP-MultiServer-Interoperable-Agent2Agent-LangGraph-AI-System](https://github.com/junfanz1/MCP-Servers)
- [Code-Interpreter-ReAct-LangChain-Agent](https://github.com/junfanz1/Code-Interpreter-ReAct-LangChain-Agent)
- [LLM-Documentation-Chatbot](https://github.com/junfanz1/LLM-Documentation-Chatbot)
- [Cognito-LangGraph-RAG](https://github.com/junfanz1/Cognito-LangGraph-RAG)
- [LangGraph-Reflection-Researcher](https://github.com/junfanz1/LangGraph-Reflection-Researcher)
- [Cursor-FullStack-AI-App](https://github.com/junfanz1/Cursor-FullStack-AI-App)
## ByteByteGo - GenAI/ML/Modern System Design Interview
System Design Interview, An Insider's Guide, Second Edition - by Alex Xu, 2020
> [Book Link](https://www.amazon.com/System-Design-Interview-insiders-Second/dp/B08CMF2CQF) | [__PDF Notes-Chinese__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/System%20Design/Notes%20on%20System%20Design.pdf)
Generative AI System Design Interview - by Ali Aminian, Hao Sheng, 2024
> [Book Link](https://www.amazon.com/Machine-Learning-System-Design-Interview/dp/1736049127) | [__Markdown Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/System%20Design/GenAI%20System%20Design%20Interview.md)
Machine Learning System Design Interview - by Ali Aminian, Alex Xu, 2023
> [Book Link](https://www.amazon.com/Machine-Learning-System-Design-Interview/dp/1736049127) | [__Markdown Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Review/blob/main/System%20Design/ML%20System%20Design%20Interview.md)
## Educative - GenAI/Modern System Design Interview
> [Educative - Grokking System Design Interview](https://www.educative.io/verify-certificate/B86jYxWPP3JhA8lAZw0B2Mhr92YjJNmG5Ty) | [__PDF Notes__](https://github.com/junfanz1/CS-Online-Course-Notes/blob/main/Grokking%20the%20System%20Design%20Interview/Grokking%20the%20System%20Design%20Interview.pdf) | [__Markdown Notes__](https://github.com/junfanz1/CS-Online-Course-Notes/blob/main/Grokking%20the%20System%20Design%20Interview/Grokking%20the%20System%20Design%20Interview.md)
> [Educative - Grokking the Modern System Design Interview](https://www.educative.io/courses/grokking-the-system-design-interview) | [__Markdown Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Overview/blob/main/System%20Design/Modern%20System%20Design.md)
> [Educative - GenAI System Design](https://www.educative.io/verify-certificate/RgxzXQFQkKyYgKrGjTX1RQpE9J3vT6) | [__Notes__](https://github.com/junfanz1/AI-LLM-ML-CS-Quant-Readings/blob/main/System%20Design/GenAI%20System%20Design.md)
计算机底层的秘密，陆小风 - 2023，电子工业出版社
> [Book Link](https://book.douban.com/subject/36370606/) | [__PDF Notes-Chinese__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Computer%20Systems/Notes%20on%20Computer%20Systems%20-%20Chinese.pdf)
# 9. Big Data and AI in Finance, Econometrics and Statistics Conference, UChicago 2024
BDAI Conference, 2024 Oct 3-5, UChicago
> [Abstract PDF](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Big%20Data%20AI%20in%20Finance%2C%20Econometrics%2C%20Statistics%20Conference%202024/BDAI-2024%20Abstracts.pdf) | [Agenda PDF](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Big%20Data%20AI%20in%20Finance%2C%20Econometrics%2C%20Statistics%20Conference%202024/BDAI-2024%20Program.pdf) | [__High Level Overview Notes PDF__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Big%20Data%20AI%20in%20Finance%2C%20Econometrics%2C%20Statistics%20Conference%202024/Big_Data_Finance_Conference_High_Level_Overview.pdf) | [__Conference Review Notes PDF__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Big%20Data%20AI%20in%20Finance%2C%20Econometrics%2C%20Statistics%20Conference%202024/Big_Data_Finance_Conference_Notes.pdf)
# 10. C++ Design Patterns and Derivatives Pricing
C++ Design Patterns and Derivatives Pricing (Mathematics, Finance and Risk, Series Number 2) 2nd Edition, by M. S. Joshi
> [Book Link](https://www.amazon.com/Patterns-Derivatives-Pricing-Mathematics-Finance/dp/0521721628) | [__PDF Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/C%2B%2B%20Design%20Patterns%20Derivatives%20Pricing/C%2B%2B%20Design%20Patterns%20Derivatives%20Pricing.pdf) | [__Markdown Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/C%2B%2B%20Design%20Patterns%20Derivatives%20Pricing/C%2B%2B%20Design%20Patterns%20Derivatives%20Pricing.md)
An Introduction to High-Frequency Finance, by Ramazan Gençay, et al.
> [Book Link](https://www.amazon.com/Introduction-High-Frequency-Finance-Ramazan-Gen%C3%A7ay/dp/0122796713) | [__PDF Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/An%20Intro%20to%20High-Frequency%20Finance/Notes%20on%20An%20Introduction%20to%20High-Frequency%20Finance.pdf) | [__Markdown Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/An%20Intro%20to%20High-Frequency%20Finance/An%20Introduction%20to%20High-Frequency%20Financ.md)
# 12. Machine Learning for Algorithmic Trading
Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition Paperback – by Stefan Jansen 2020
> [Book Link](https://www.amazon.com/Machine-Learning-Algorithmic-Trading-alternative/dp/1839217715) | [__PDF Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/ML%20for%20Algorithmic%20Trading/Notes%20on%20Machine%20Learning%20for%20Algorithmic%20Trading.pdf) | [__Markdown Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/ML%20for%20Algorithmic%20Trading/Notes%20on%20Machine%20Learning%20for%20Algorithmic%20Trading.md)
# 13. Stochastic Volatility Modeling
Stochastic Volatility Modeling (Chapman and Hall/CRC Financial Mathematics Series) 1st Edition, by Lorenzo Bergomi
> [Book Link](https://www.amazon.com/Stochastic-Volatility-Modeling-Financial-Mathematics/dp/1482244063) | [__PDF Char 1 Intro__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Stochastic%20Volatility%20Modeling/Stochastic%20Volatility%20Modeling%20-%20Char%201%20Introduction%20Notes.pdf) | [__Markdown Char 1 Intro__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Stochastic%20Volatility%20Modeling/Stochastic%20Volatility%20Modeling%20-%20Char%201%20Introduction%20Notes.md) | [__PDF Char 2 Local Vol__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Stochastic%20Volatility%20Modeling/Stochastic%20Volatility%20Modeling%20-%20Char%202%20Local%20Volatility%20Notes.pdf) | [__Markdown Char 2 Local Vol__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Stochastic%20Volatility%20Modeling/Stochastic%20Volatility%20Modeling%20-%20Char%202%20Local%20Volatility%20Notes.md)
# 14. Quant Job Interview Questions
Quant Job Interview Questions and Answers (Second Edition) – by Mark Joshi 2013
> [Book Link](https://www.amazon.com/Quant-Interview-Questions-Answers-Second/dp/0987122827) | [__Markdown Notes__](https://github.com/junfanz1/Quant-Books-Notes/blob/main/Quant%20Job%20Interview%20Q%26A/Quant%20Essentials%20Takeaways.md)
- [__Cloud Platform Notes__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/Quant%20Job%20Interview%20Q%26A/Cloud.pdf) | [__Quant Notes__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/Quant%20Job%20Interview%20Q%26A/Quant.pdf) | [__FX Exotic Derivatives Notes__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/Quant%20Job%20Interview%20Q%26A/FX%20Exotic%20Derivatives.pdf) | [__Risk Methodologies Notes__](https://github.com/junfanz1/AI-ML-CS-Quant-Readings/blob/main/Quant%20Job%20Interview%20Q%26A/Risk%20Methodologies.pdf)
---
[](https://www.star-history.com/#junfanz1/AI-LLM-ML-CS-Quant-Readings&Date)