Beginners Page 2031 - DEV Community

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UPDATED AUGUST 2, 2019

This tag is dedicated to beginners to programming, development, networking, or to a particular language. Everything should be geared towards that!

For Questions...

Consider using this tag along with #help, if...

You are new to a language, or to programming in general,
You want an explanation with NO prerequisite knowledge required.
You want insight from more experienced developers.

Please do not use this tag if you are merely new to a tool, library, or framework.

See also, #explainlikeimfive

For Articles...

Posts should be specifically geared towards true beginners (experience level 0-2 out of 10).
Posts should require NO prerequisite knowledge, except perhaps general (language-agnostic) essentials of programming.
Posts should NOT merely be for beginners to a tool, library, or framework.

If your article does not meet these qualifications, please select a different tag.

Promotional Rules

Posts should NOT primarily promote an external work. This is what Listings is for.
Otherwise accepable posts MAY include a brief (1-2 sentence) plug for another resource at the bottom.
Resource lists ARE acceptable if they follow these rules:
- Include at least 3 distinct authors/creators.
- Clearly indicate which resources are FREE, which require PII, and which cost money.
- Do not use personal affiliate links to monetize.
- Indicate at the top that the article contains promotional links.

If you're writing for this tag, we recommend you read this article.

If you're asking a question, read this article.

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Elanat Framework

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Shehzad Hussain

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Uncontrolled vs Controlled React Components

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Understanding JavaScript Execution Context

#webdev #javascript #beginners #programming

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Mitchell Mutandah

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The Hilarious Guide to Career Sabotage

#webdev #developer #beginners #programming

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Introduction to CSS: Styling the Web

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May 28 '24

What is the useRef() Hook?

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Learning AWS Day by Day — Day 77 — Amazon Redshift

#aws #cloud #cloudcomputing #beginners

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Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling

#machinelearning #ai #beginners #datascience

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XMoE: Sparse Models with Fine-grained and Adaptive Expert Selection

#machinelearning #ai #beginners #datascience

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Many-Shot In-Context Learning

#machinelearning #ai #beginners #datascience

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Bring Your Own KG: Self-Supervised Program Synthesis for Zero-Shot KGQA

#machinelearning #ai #beginners #datascience

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ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

#machinelearning #ai #beginners #datascience

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May 28 '24

Efficient Encoder-Decoder Transformer Decoding for Decomposable Tasks

#machinelearning #ai #beginners #datascience

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