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title: Best Data Science Central posts — September 2024 | daily.dev
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# Best of Data Science Central — September 2024

1. 1  
[](https://daily.dev/posts/your-personal-genai-innovation-curriculum-tlls6f7ld "Your Personal GenAI Innovation Curriculum")  
Article  
![Avatar of ds_central](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/ds_central)Data Science Central · 2y  
Your Personal GenAI Innovation Curriculum  
A comprehensive curriculum designed to help individuals leverage Generative AI (GenAI) tools for innovation and personal development. The curriculum offers a structured pathway from foundational knowledge to advanced applications, emphasizing critical thinking, ethical alignment, and strategic prompt engineering. It aims to transform the use of GenAI tools from merely improving productivity to driving significant innovative outcomes in various domains.  
39  
1
2. 2  
[](https://daily.dev/posts/30-features-that-dramatically-improve-llm-performance-part-2-eyeuo87be "30 Features that Dramatically Improve LLM Performance – Part 2")  
Article  
![Avatar of ds_central](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/ds_central)Data Science Central · 2y  
30 Features that Dramatically Improve LLM Performance – Part 2  
The post explores 10 additional features that significantly enhance LLM performance, particularly in terms of speed, latency, relevancy, memory use, and security. It discusses distillation for concise outputs, reproducibility with PRNGs, explainable AI using few parameters, and the benefits of no-training LLMs. The author also touches on the advantages of transformer-free LLMs, taxonomy-based evaluation, prompt data augmentation, and the importance of backend over frontend engineering. The importance of cautious use of NLP tools to avoid glitches is also highlighted.  
33
3. 3  
[](https://daily.dev/posts/large-ai-apps-optimizing-the-databases-behind-the-scenes-ghsd6dmgm "Large AI Apps: Optimizing the Databases Behind the Scenes")  
Article  
![Avatar of ds_central](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/ds_central)Data Science Central · 2y  
Large AI Apps: Optimizing the Databases Behind the Scenes  
The post explores various types of databases beneficial for RAG and LLM applications, such as vector, graph, JSON, and object-oriented databases. It offers practical tips for optimizing these databases to enhance performance, including switching to high-performance databases, efficient encoding, data distillation, leveraging cloud and GPU, and using in-memory queries and approximate nearest neighbor search.  
10

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