<!-- mobian-agent-page publisher="dailydev" canonical="https://daily.dev/sources/dailydoseofds/best-of/2025/02" -->

---
title: Best Daily Dose of Data Science | Avi Chawla | Substack...
description: The most upvoted Daily Dose of Data Science | Avi Chawla | Substack posts from February 2025, curated by the daily.dev community.
canonical: https://daily.dev/sources/dailydoseofds/best-of/2025/02
twitter:card: summary_large_image
twitter:site: @dailydotdev
og:url: https://daily.dev/sources/dailydoseofds/best-of/2025/02
og:type: website
og:site_name: daily.dev
og:title: Best Daily Dose of Data Science | Avi Chawla | Substack posts — February 2025 | daily.dev
og:description: The most upvoted Daily Dose of Data Science | Avi Chawla | Substack posts from February 2025, curated by the daily.dev community.
og:image: https://media.daily.dev/image/upload/s--VAY5ToZt--/f_auto/v1724209435/public/daily.dev%20-%20open%20graph
---

# Best of Daily Dose of Data Science | Avi Chawla | Substack — February 2025

1. 1  
[](https://daily.dev/posts/ai-agent-crash-course-part-1-48mrhddpo "AI Agent Crash Course—Part 1")  
Article  
![Avatar of dailydoseofds](https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds)Daily Dose of Data Science | Avi Chawla | Substack · 2y  
AI Agent Crash Course—Part 1  
In this crash course, learn about AI agents and their implementation. It covers the fundamentals, memory for agents, agentic flows, guardrails, implementing agentic design patterns, and optimizing agents for production. The aim is to build autonomous systems that can reason, plan, take actions, and correct themselves, going beyond the capabilities of standalone generative models.  
199  
1
2. 2  
[](https://daily.dev/posts/16-techniques-to-build-real-world-rag-systems-d2s6fskvb "16 Techniques to Build Real-world RAG Systems")  
Article  
![Avatar of dailydoseofds](https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds)Daily Dose of Data Science | Avi Chawla | Substack · 2y  
16 Techniques to Build Real-world RAG Systems  
Scaling a prototype RAG system for real-world use presents significant challenges, such as performance bottlenecks and inefficient retrieval. This guide offers 16 practical techniques to help developers overcome these issues across five key pillars. It also highlights five agentic AI design patterns, including reflection, tool use, ReAct, planning, and multi-agent patterns, which enable LLMs to refine outputs, gather information, and subdivide tasks more effectively.  
188
3. 3  
[](https://daily.dev/posts/open-source-python-development-landscape-xotdr7gbs "Open-source Python Development Landscape")  
Article  
![Avatar of dailydoseofds](https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds)Daily Dose of Data Science | Avi Chawla | Substack · 2y  
Open-source Python Development Landscape  
Explore the essential tools for various stages of Python development, including dependency and package managers, monitoring and profiling, virtual environments, linters and style checkers, type checkers, logging, testing, debugging, code refactoring, and code security. These tools are crucial for improving development workflow and code quality.  
88  
3
4. 4  
[](https://daily.dev/posts/4-ways-to-test-ml-models-in-production-wclbwd6mq "4 Ways to Test ML Models in Production")  
Article  
![Avatar of dailydoseofds](https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds)Daily Dose of Data Science | Avi Chawla | Substack · 2y  
4 Ways to Test ML Models in Production  
Testing machine learning models in production is crucial for reliability. Four key strategies are A/B testing, canary testing, interleaved testing, and shadow testing. These methods allow models to be tested on real-world data while minimizing risk and user impact. Tools like Maxim can aid in simulating, evaluating, and observing AI agents for better performance before deployment.  
45  
2
5. 5  
[](https://daily.dev/posts/hands-on-agentic-rag-using-deepseek-r1-v6pt7q0kc "[Hands-on] Agentic RAG Using DeepSeek-R1")  
Article  
![Avatar of dailydoseofds](https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds)Daily Dose of Data Science | Avi Chawla | Substack · 2y  
\[Hands-on\] Agentic RAG Using DeepSeek-R1  
Learn how to build an intelligent RAG application using DeepSeek-R1 that offers vision-based indexing and supports over 100 file formats without requiring OCR or text extraction. The tutorial walks through the setup of a local DeepSeek model, integrating tools like Qdrant and FireCrawl, and defining agents for retrieving context and generating responses using CrewAI.  
30

[See all Daily Dose of Data Science | Avi Chawla | Substack archives](/sources/dailydoseofds/best-of)

```json
{"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]}
{"@context":"https://schema.org","@graph":[{"@type":"CollectionPage","@id":"https://daily.dev/sources/dailydoseofds/best-of/2025/02#page","url":"https://daily.dev/sources/dailydoseofds/best-of/2025/02","name":"Best Daily Dose of Data Science | Avi Chawla | Substack Posts — February 2025","description":"The most upvoted Daily Dose of Data Science | Avi Chawla | Substack posts from February 2025, curated by the daily.dev community.","isPartOf":{"@type":"WebSite","url":"https://daily.dev"}},{"@type":"ItemList","@id":"https://daily.dev/sources/dailydoseofds/best-of/2025/02#items","numberOfItems":5,"itemListElement":[{"@type":"ListItem","position":1,"url":"https://daily.dev/posts/ai-agent-crash-course-part-1-48mrhddpo","name":"AI Agent Crash Course—Part 1"},{"@type":"ListItem","position":2,"url":"https://daily.dev/posts/16-techniques-to-build-real-world-rag-systems-d2s6fskvb","name":"16 Techniques to Build Real-world RAG Systems"},{"@type":"ListItem","position":3,"url":"https://daily.dev/posts/open-source-python-development-landscape-xotdr7gbs","name":"Open-source Python Development Landscape"},{"@type":"ListItem","position":4,"url":"https://daily.dev/posts/4-ways-to-test-ml-models-in-production-wclbwd6mq","name":"4 Ways to Test ML Models in Production"},{"@type":"ListItem","position":5,"url":"https://daily.dev/posts/hands-on-agentic-rag-using-deepseek-r1-v6pt7q0kc","name":"[Hands-on] Agentic RAG Using DeepSeek-R1"}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Sources","item":"https://daily.dev/sources"},{"@type":"ListItem","position":3,"name":"Daily Dose of Data Science | Avi Chawla | Substack","item":"https://daily.dev/sources/dailydoseofds"},{"@type":"ListItem","position":4,"name":"Best of","item":"https://daily.dev/sources/dailydoseofds/best-of"},{"@type":"ListItem","position":5,"name":"February 2025"}]}]}
```

