λ Haskell

Pure Functions, Type Classes, Monads, Lazy Evaluation, GHC

How to Convert RTF to PDF in Java: A Step-by-Step Guide
e-iceblue.com·19h·
Discuss: DEV
🔧haskell
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Proof of the Riemann Hypothesis. - Phaztwø
i.redd.it·1d·
Discuss: r/compsci
🔬Hypothesis Testing
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Mount Mayhem at Netflix: Scaling Containers on Modern CPUs
netflixtechblog.medium.com·10h·
Discuss: Hacker News
🔵Blue-Green Deployment
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Is AI After My Job? Navigating the Future of Research Software Engineering
software.ac.uk·19h
🌪️Chaos Engineering
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Python + ClojureScript: Pyodide Integration with Scittle
clojurecivitas.github.io·3d·
Discuss: Hacker News
🔵Clojure
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The Production Generative AI Stack: Architecture and Components
thenewstack.io·1d
⚙️Performance Profiling
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How to Use GPT-5 Effectively
towardsdatascience.com·17h
🎲Property-Based Testing
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Cons Should Not Cons Its Arguments, Part II: Cheney on the MTA
web.archive.org·5d·
Discuss: Hacker News
🎓Scheme
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dbeaver/dbeaver
github.com·4h
👀Code Reviews
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Spooky Pumpkin
github.com·56m·
Discuss: DEV
📝Org-Mode
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Hillnote as an easy way to create Claude Skills
reddit.com·10h·
Discuss: r/ClaudeAI
📝Org-Mode
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<p>**Abstract:** This paper presents a novel framework, Autonomous Celestial Calibration &#038; Ephemeris Refinement via Bayesian Neural Network Ensemble (BCERE...
freederia.com·1d
⛓️MCMC
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Day 1 of daily coding: Functions is java
dev.to·2d·
Discuss: DEV
🎓Scheme
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A Guide to the Best Java Machine Learning Libraries
dev.to·1d·
Discuss: DEV
🤖Scikit-learn
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Java vs JavaScript vs Python: Which Is Best for Test Automation?
dev.to·17h·
Discuss: DEV
🔴Test-Driven Development
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Course Transistion from Javascrip to TypeScript
github.com·6d·
Discuss: r/typescript
🔧haskell
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Measuring Aleatoric and Epistemic Uncertainty in LLMs: Empirical Evaluation on ID and OOD QA Tasks
arxiv.org·2d
⛓️MCMC
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How do I actually learn programming?
reddit.com·1d·
Discuss: r/godot
🎓Scheme
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VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework forUnseen Concept Manipulation
paperium.net·17h·
Discuss: DEV
📐Gini Coefficient
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From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilers
arxiv.org·2d
🔗Parser Combinators
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