I built 10 ML algos from scratch because fit() predict() are not enough
Details
- External ID
- 48461956
- Source
- HN
- Company
- —
- Product
- I built 10 ML algos from scratch because fit() predict() are not enough
- Website domain
- github.com
- Launched
- June 9, 2026
- Cohort
- —
- Upvotes
- 6
- Upvotes percentile
- 0.31420765027322406
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Enrichment
- Theme
- ML inference and model optimization
- Vertical
- Horizontal
- Function
- Dev tools
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Hobby / open-source project
- Normalized one-liner
- machine learning algorithms library
- Manually corrected
- False
Could you build this?
No Writing 10 fundamental machine learning algorithms from mathematical first principles without existing libraries requires rigorous understanding of linear algebra, multivariable calculus, and numerical optimization.
What it would actually take: Implementing algorithms such as SVMs with quadratic programming solvers, backpropagation from scratch with automatic differentiation, tree-based models with custom splitting criteria, and EM/clustering requires deriving loss gradients and handling numerical stability issues (e.g., vanishing/exploding gradients, log-sum-exp tricks). The codebase requires pure Python/NumPy or C/Rust implementations with custom vectorization and optimization routines rather than relying on scikit-learn or PyTorch.
Discussion
2 comments analyzed.
Competitors mentioned: Sklearn, PyTorch
Competitors
Other products that read as similar to this one — 21 launches clear the similarity bar, closest 8 shown.
Attention rank: #10 of 22 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 203 days after the earliest competitor.
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Other launches for this product
- No other launches for this product.
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