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"A journey of a thousand miles begins with a single step." -Chinese Proverb

submission guidelines

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.

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Sachin Kr. Rajput

Jan 13

L1 vs L2 Regularization: The Minimalist vs The Diplomat — Two Philosophies That Shape Your Model

#machinelearning #ai #beginners #datascience

10 min read

Sachin Kr. Rajput

Jan 13

Regularization: The Art of Telling Your Model to Calm Down and Stop Overthinking

#machinelearning #ai #beginners #datascience

10 min read

Sachin Kr. Rajput

Jan 13

Cross-Validation: Why Testing Your Model Once Is Like Judging a Restaurant by a Single Bite

#machinelearning #ai #beginners #datascience

11 min read

Sachin Kr. Rajput

Jan 13

Batch vs Mini-Batch vs Stochastic Gradient Descent: Three Hikers, Three Strategies, One Mountain

#machinelearning #ai #beginners #datascience

10 min read

Rushikesh Bodakhe

Jan 13

Looking for Developer Feedback: Open Issues in Vizora (Schema Intelligence Tool)

#webdev #ai #programming #beginners

1 min read

Sachin Kr. Rajput

Jan 13

Learning Rate: The One Number That Can Make or Break Your Entire Model

#machinelearning #ai #beginners #datascience

10 min read

Shubh

Dec 9 '25

Built DockMate: A terminal UI for Docker (27 stars in 3 days)

#devops #docker #opensource #beginners

1 min read

igbojionu

Jan 13

PYTHON FUNDAMENTALS | From Basics to Real-World Applications

#beginners #learning #python #tutorial

17 min read

Sachin Kr. Rajput

Jan 13

Gradient Descent: How to Find the Lowest Point in a Valley While Completely Blindfolded

#machinelearning #ai #beginners #datascience

10 min read

Sachin Kr. Rajput

Jan 13

Loss Functions: The Brutally Honest Friend Your Model Desperately Needs

#machinelearning #ai #beginners #datascience

9 min read

Sachin Kr. Rajput

Jan 13

Classification vs Regression: The Doctor Who Gives Answers vs The Doctor Who Gives Numbers

#machinelearning #ai #beginners #datascience

9 min read

Sachin Kr. Rajput

Jan 13

Parametric vs Non-Parametric Models: The GPS vs The Taxi Driver

#machinelearning #ai #beginners #datascience

9 min read

Rahul Raj

Dec 9 '25

Different Ways to Find Even and Odd Numbers

#beginners #java #tutorial

2 min read

Sachin Kr. Rajput

Jan 13

Overfitting & Underfitting: Why Your Model Aced the Practice Test But Failed the Real Exam

#machinelearning #ai #beginners #datascience

10 min read

Sachin Kr. Rajput

Jan 13

The Bias-Variance Tradeoff: Why Your Model is Either Too Dumb or Too Smart

#machinelearning #ai #beginners #datascience

7 min read

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