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genpark-dense-feedforward-mlp-backprop-skill

Multi-layer perceptron (MLP) feedforward inference with Xavier/Glorot initialization and activations

Details

External ID
1392364598
Source
GITHUB
Company
—
Product
genpark-dense-feedforward-mlp-backprop-skill
Website domain
github.com
Launched
Sept. 28, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
agent-skills, ai-inference, deep-learning, feedforward, machine-learning, mcp, mlp, neural-networks, python-standard-library, relu, xavier-initialization
Fetched at
Sept. 30, 2026, 1:02 a.m.
Updated at
Sept. 30, 2026, 1:02 a.m.

Enrichment

Theme
ML inference and model optimization
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
feedforward neural network inference engine for developers
Manually corrected
False

Could you build this?

Yes A standalone pure-Python or NumPy implementation of a multi-layer perceptron with Xavier initialization and backprop is a textbook CS exercise that LLMs output instantly.

Competitors

Other products that read as similar to this one — 1582 launches clear the similarity bar, closest 8 shown.

Attention rank: #1343 of 1583 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 334 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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