Arena Shawn on Medium curated some lists

Arena Shawn

Arena Shawn

Learning DS and ML

698 stories

Arena Shawn

Causal

1 story

Arena Shawn

Math

207 stories

Arena Shawn

LLM

368 stories

Arena Shawn

Projects

256 stories

An overview of the RAG pipeline. For documents storage: input documents -> text chunks -> encoder model -> vector database. For LLM prompting: User question -> encoder model -> vector database -> top-k relevant chunks -> generator LLM model. The LLM then answers the question with the retrieved context.

Arena Shawn

Data Visualization

210 stories

Arena Shawn

Python Data Science

325 stories

Arena Shawn

Intermediate Python

243 stories

Arena Shawn

Job seeking

117 stories

Arena Shawn

Business Analysis

68 stories

Arena Shawn

Machine Laerning

547 stories

Arena Shawn

Prompt engineering

34 stories

Arena Shawn

Time series forecasting

65 stories

Arena Shawn

ImageGen AI

24 stories

Arena Shawn

Good Books

7 stories

Arena Shawn

Datasets

4 stories

Arena Shawn

SQL

57 stories

Arena Shawn

Web Development

47 stories

Arena Shawn

NLP

129 stories

Arena Shawn

Content Creation

7 stories

Arena Shawn

Arena Shawn

Physicist and Silicon Engineer turned Classical Painter, now on the exciting new journey again in the Data Science world

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