Search Results for "problem a"
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358 projects for "problem a" with 1 filter applied:
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MathModelAgent
An Agent Designed for Mathematical Modeling
MathModelAgent is an AI agent system designed specifically for assisting with mathematical modeling tasks and academic problem solving. The platform automates the process of analyzing mathematical problems, constructing models, generating code for simulations or computations, and producing a complete research-style report. The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation, and paper writing. ... -
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How-To-Ask-Questions-The-Smart-Way
Correctly propose technical questions and get the answers you want
...The guide is particularly valuable for beginners who are learning how to interact in open-source communities and forums. By improving communication, it increases the likelihood of receiving helpful and accurate responses. Overall, it serves as a foundational resource for effective problem-solving and collaboration in software development. -
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Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
...Because it’s framed around beating baseline scores — and even outperforming previous automated systems — it encourages both deep knowledge of Python and creative problem-solving. -
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Python-programming-exercises
100+ Python challenging programming exercises
Python-programming-exercises is an educational repository containing more than 100 Python programming challenges. It is designed to help learners practice problem solving through short exercises rather than full applications. The exercises cover fundamentals such as strings, numbers, loops, lists, dictionaries, functions, regular expressions, file handling, classes, generators, and algorithmic thinking. Many problems include both a prompt and a suggested solution, making the repository useful for self-study and interview-style practice. ... -
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pytudes
Python programs, usually short, of considerable difficulty
...The repository includes readable solutions, experiments, notebooks, and scripts that cover algorithms, puzzles, probability, search, language processing, simulation, and mathematical reasoning. It is useful for programmers who want to study elegant Python code while learning how experienced developers approach problem solving. Many examples emphasize clarity and compactness rather than framework-heavy engineering. pytudes is best understood as a learning library, a coding style reference, and a set of practical programming studies. -
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colleague-skill
Transform a cold separation into a warm Skill
colleague-skill is a specialized agent skill designed to simulate a collaborative teammate within AI-driven workflows, enabling agents to behave more like human colleagues in problem-solving scenarios. The project focuses on enhancing interaction quality by introducing role-based behavior, contextual awareness, and cooperative task execution. It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. ... -
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Reflexion
Reflexion: Language Agents with Verbal Reinforcement Learning
Reflexion is a research-oriented AI framework that focuses on improving the reasoning and problem-solving capabilities of language model agents through iterative self-reflection and feedback loops. Instead of relying solely on a single-pass response, Reflexion enables agents to evaluate their own outputs, identify errors, and refine their reasoning over multiple iterations, leading to more accurate and reliable results. The framework introduces a mechanism where agents maintain a memory of past attempts and use that memory to guide future decisions, effectively simulating a learning process without requiring traditional model retraining. ... -
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FDE-Book-of-Forward-Deployed-Engineer
Frontier Deployment Engineer) Beginner's Guide from Scratch
...It explains the Forward Deployed Engineer role as the bridge between a product’s capabilities and a customer’s real operational needs. The chapters follow a complete delivery journey, from selecting the right problem and winning a customer to deployment, renewal, expansion, and repeatable scaling. The work draws on primary materials, job descriptions, industry research, practitioner accounts, and more than one hundred documented company cases. Dedicated sections examine Palantir’s influence, modern AI companies, customer-facing engineering methods, metrics, and professional ethics. ... -
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Computational Thinking
Introduction to computational thinking with Julia
Computational Thinking is an open source MIT course repository that teaches computational problem-solving through the Julia programming language. The course integrates mathematics, computing, and real-world applications into a unified curriculum, making it suitable for students across science, engineering, and data-driven fields. It emphasizes learning how to translate problems into computational terms and developing algorithms and models to analyze them effectively. -
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Claude Code Best V3
The original Claude Code is runnable and buildable
...It supports plugin-based extensions that enhance its capabilities with specialized commands and workflows. The architecture emphasizes productivity, enabling developers to offload routine tasks and focus on higher-level problem-solving. It also integrates with existing development tools, making it adaptable to different workflows and environments. -
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Hypermind
The high-availability solution to a problem that doesn't exist
Hypermind is a whimsical yet technically intriguing decentralized application that combines a peer-to-peer (P2P) network counter with ephemeral chat functionality, built to “solve” the meta-problem of tracking how many peers are running its container in a decentralized mesh. There’s no central server or database; instead, Hypermind leverages a Distributed Hash Table (DHT) using Hyperswarm to discover peers and maintain approximate counts of active nodes, architected to be a fully decentralized service. Alongside counting nodes, the project also supports ephemeral chat over its mesh network, allowing users to send messages directly to local peers or broadcast via a gossip protocol without storing chat history. ... -
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huihut interview
A summary of C/C++ technical interview basics
...The repo is designed so learners can practice real interview scenarios, compare approaches, and internalize foundational concepts that are frequently tested by tech companies. Many entries include both the problem statement and one or more reference implementations, offering insights into time/space complexity and tradeoffs between competing strategies. It’s organized to be approachable whether you’re a student preparing for your first internship or an experienced engineer brushing up on fundamentals before a big interview round. -
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LeetCode Animation
Demonstrate all the questions on LeetCode in the form of animation
...The goal of the project is to help learners understand complex algorithmic concepts intuitively by showing step-by-step animated explanations instead of relying solely on static code or text. Each animation corresponds to a specific problem and illustrates how data structures and algorithms operate dynamically, making it easier to grasp their underlying logic. The project also includes a curated set of 40 problems from the “Sword Pointing to Offer” series—commonly asked in technical interviews—accompanied by detailed analyses and visual breakdowns. These materials are designed for both beginners starting their algorithm journey and experienced developers seeking to reinforce their understanding. ... -
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book-to-skill
Turn any technical book PDF into a Claude Code skill
...It includes an extraction script and a SKILL.md workflow that guides how the resulting content should be used. The goal is not simply to summarize a book, but to make its knowledge available during problem solving and implementation. book-to-skill is best suited for developers and researchers who want AI assistants to work from specific long-form source material. -
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Open Multi-Agent
One runTeam() call from goal to result
Open Multi-Agent is a flexible framework designed to enable the creation and coordination of multiple AI agents working together to solve complex tasks through collaboration. It focuses on distributing responsibilities across specialized agents, each handling a specific part of a problem, such as planning, execution, or validation. The system emphasizes modularity, allowing developers to define agent roles, communication protocols, and workflows. It supports iterative collaboration, where agents exchange information and refine outputs collectively. The architecture is designed to be extensible, enabling integration with external tools and APIs to expand agent capabilities. ... -
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WFGY 3.0
A tension reasoning engine over 131 S-class problems
WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply... -
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Daily Interview
Datawhale members have compiled a book covering machine learning
...The repository is organized in a structured format that encourages developers to practice solving problems regularly while building a deeper understanding of underlying concepts. Many of the problems include explanations, references, or links to additional learning resources that help users study relevant theory and improve problem-solving skills. The project is particularly useful for developers preparing for coding interviews at technology companies, as it provides a continuous stream of practice material organized by topic and difficulty level. -
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Kimi K2
Kimi K2 is the large language model series developed by Moonshot AI
...The model family includes variants like a foundational base model that researchers can fine-tune for specific use cases and an instruct-optimized variant primed for general-purpose chat and agent-style interactions, offering flexibility for both experimentation and deployment. With its high-dimensional attention mechanisms and expert routing, Kimi-K2 excels across benchmarks in live coding, math reasoning, and problem solving. -
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Napkin Math
Techniques and numbers for estimating system's performance
Napkin Math is a technical reference project for estimating software system performance from first principles. It collects practical numbers, benchmark-style measurements, and mental models that help engineers make fast back-of-the-envelope calculations. The project is useful for questions like how much memory throughput matters, how long storage operations may take, what network latency to expect, or how expensive logging could become at high request volume. It treats these values as... -
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ARIS
Lightweight Markdown-only skills for autonomous ML research
...It integrates with AI tools such as Claude Code to generate solutions, analyze results, and improve outputs over time. The project emphasizes long-running workflows that can explore problem spaces more deeply than manual intervention would typically allow. It also highlights the potential of autonomous agents to handle repetitive or exploratory tasks that would otherwise require significant human effort. The framework is particularly relevant for developers interested in automated experimentation, continuous learning systems, and AI-driven productivity. -
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fe-advanced-interview
A Guide to Advanced Front-End Interviews
fe-advanced-interview is a comprehensive front-end engineering interview preparation repository focused on advanced web development concepts, system design, and real-world technical problem solving. The project compiles high-level interview questions and explanations covering JavaScript internals, browser rendering, networking, performance optimization, frameworks, architecture, and engineering best practices. Unlike beginner-focused interview guides, it emphasizes deeper understanding of how front-end technologies work internally and how large-scale applications are designed and maintained. ... -
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Watlings
Learn WebAssembly by writing small programs
...Inspired by projects like Rustlings, it provides a collection of small, focused challenges that help users understand how WebAssembly works at a low level, including instructions, memory management, and control flow. Each exercise presents partially completed code that the user must fix or complete, reinforcing learning through hands-on problem solving rather than passive reading. The platform runs entirely in the browser, allowing users to experiment with WAT code and see immediate results without installing any tools. It is particularly useful for developers who want to understand how high-level languages compile down to WebAssembly or who are interested in systems-level programming concepts. -
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SuperPrompt
Experimental prompt framework exploring reasoning structures in AI
...Its main concept revolves around a highly structured prompt format that includes tagged sections for reasoning, analysis, conceptual expansion, and recursive thinking patterns. These sections act as a kind of meta-instruction system intended to influence how an AI model approaches problem solving and conceptual exploration. SuperPrompt also incorporates ideas from mathematics, recursion, abstract algebra, and theoretical reasoning to encourage models to perform multi-step conceptual synthesis rather than simple direct responses. -
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LeetCode Book
Comprehensive study guide for coding interviews
...Many entries include template code and “swap-in” variations, helping you recognize how the same technique adapts across similar problems. The book also emphasizes problem-solving habits like deriving invariants, choosing appropriate data structures, and verifying with small counterexamples. It’s suitable for newcomers building fundamentals and for experienced engineers polishing timing and correctness under interview pressure. -
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Zero to Mastery Machine Learning
All course materials for the Zero to Mastery Machine Learning
...The project provides a structured curriculum designed to teach machine learning and data science using Python through hands-on projects and interactive notebooks. The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from problem definition to model deployment. The course introduces essential tools such as NumPy, pandas, Matplotlib, and scikit-learn before moving on to deep learning with frameworks like TensorFlow and Keras. It also includes milestone projects that demonstrate how to build end-to-end machine learning systems using real datasets, including classification and regression tasks.
