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Introduction to Platform Engineering: Exploring Key Concepts, Principles, and Benefits

Team DSH3 years ago3 years ago010 mins

Platform engineering distinguishes itself through a systematic approach towards designing, building, and maintaining platforms, providing a solid foundation for multiple applications and services.

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Thinking Fast & Slow: Tests for Large Language Models Like ChatGPT-4

Team DSH3 years ago3 years ago011 mins

In this article, we explore the application of principles and cognitive tests from the book “Thinking, Fast and Slow” by Nobel laureate Daniel Kahneman to evaluate the cognitive capabilities of ChatGPT-4.

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13 Prompt Engineering Tips

Team DSH3 years ago3 years ago09 mins

This article delves into various strategies for prompt engineering, with the aim of helping users to optimize their interactions with AI, whether the goal is to seek information, create engaging content, or simply to foster an interesting dialogue.

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smol ai developer: Text to Codebase

Team DSH3 years ago05 mins

smol developer is a prototype of a junior developer agent that scaffolds an entire codebase for you once given a product specification.

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OLTP vs OLAP: Key Differences, Use Cases, and Database Engine Overviews

Team DSH3 years ago3 years ago010 mins

In this article, we delve into an overview of OLTP and OLAP, explore their key differences, use cases, and offer insights into when one should be chosen over the other.

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Getting Started with Weka

Team DSH3 years ago3 years ago011 mins

In this blog post, we’ll delve into a popular, free, and open-source toll called Weka, which is extensively used in data mining and machine learning tasks.

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The Emergent Abilities of Large Language Models: Mirage or Milestone?

Team DSH3 years ago3 years ago013 mins

Emergent abilities, as the term suggests, are capabilities that emerge or manifest in Large Language Models (LLMs) as they scale up in size and complexity.

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Understanding Bias in Data Science

Team DSH3 years ago3 years ago011 mins

Bias in data science is like a silent operator. It exists subtly in many forms, from data collection to interpretation, and if not checked, it can derail the objectivity and reliability of your analyses.

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A Beginner’s Guide to Feature Engineering with Python: Creating Relevant Features

Team DSH3 years ago3 years ago012 mins

n this tutorial, we will delve into the basics of feature engineering with Python and how to create relevant features.

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3 Python Tips that Machine Learning Engineers Should Know

Team DSH3 years ago3 years ago08 mins

In this article, we will walk you through three Python tips that every machine learning engineer should have in their toolkit.

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Bias-Variance Trade-off: Modern Relevance

Team DSH3 years ago3 years ago06 mins

This fundamental principle is crucial in comprehending the limitations and potential of any data analysis, and it plays a critical role in modern data science.

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Prompt Engineering for ELIZA [eBook]

Team DSH3 years ago12 months ago03 mins

Are you seeking to explore the comical intersections of historic AI and modern language models? Our ebook, Prompt Engineering for ELIZA, promises a unique blend of education and entertainment that explores the fundamentals of AI and prompt engineering through the lens of ELIZA, a 1960s chatbot.

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Recent Posts

  • Hybrid AI model crafts smooth, high-quality videos in seconds
  • Why Do LLMs Have Emergent Properties?
  • How to Build Your Own Local AI: Create Free RAG and AI Agents with Qwen 3 and Ollama
  • Ranked: The Most Visited Websites in the World
  • How to Create Serverless AI Agents with Langbase Docs MCP Server in Minutes

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