Search Results for "morse code practice" - Page 5
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Showing 231 open source projects for "morse code practice"
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microStudio
Free, open source game engine online
...But you can also code in JavaScript, Python, or Lua if you prefer. -
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ICCV2023-Paper-Code-Interpretation
ICCV2021/2019/2017 Paper/Code/Interpretation/Live Broadcast Collection
ICCV2023-Paper-Code-Interpretation is a curated repository that provides explanations and interpretations of code associated with research papers presented at the International Conference on Computer Vision (ICCV) 2023. The project focuses on helping researchers and students better understand how complex computer vision algorithms described in academic papers are implemented in practice. -
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D2L.ai
Interactive deep learning book with multi-framework code
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth to... -
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MorseCodeConverter
MorseCodeConverter lets anyone translate text to Morse code easily.
MorseCodeConverter allows users to convert text into Morse code, providing an interactive way to explore and work with Morse code translations. -
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TerraCognita
Reads from existing public and private cloud providers
Imports your current Cloud infrastructure to an Infrastructure As Code Terraform configuration (HCL) or/and to a Terraform State. At Cycloid, Infrastructure As Code is in the company's DNA since the beginning. To help our new customers adopt this best practice, we decided to build Terracognita to convert an existing infrastructure on Cloud Infrastructure into Terraform code in an automated way, relying on Terraform providers built by the community. -
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Python Data Science Handbook
Python Data Science Handbook: full text in Jupyter Notebooks
The Python Data Science Handbook is a comprehensive collection of Jupyter notebooks written by Jake VanderPlas covering fundamental Python libraries for data science, including IPython, NumPy, Pandas, Matplotlib, Scikit-Learn and more. The project is designed for data scientists, researchers, and anyone transitioning into Python-based data work; it assumes you already know basic Python and focuses more on how to use the ecosystem effectively. Each chapter is a standalone Jupyter notebook,... -
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Cheetah
AI macOS app for real-time coding interview coaching assistance
Cheetah is an AI-powered macOS application designed to assist users during software engineering interview practice through real-time coaching capabilities. It integrates audio transcription and AI-generated responses to help users navigate technical interview questions as they happen. Cheetah uses a local speech-to-text engine based on Whisper to capture and transcribe conversations in real time, enabling it to understand interviewer prompts. -
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LibreSSL for Windows
LibreSSL is a fork of OpenSSL that improves code quality and security
LibreSSL is a version of the TLS/crypto stack forked from OpenSSL in 2014, with goals of modernizing the codebase, improving security, and applying best practice development processes. GOST Support: GOST 28147-89 - Block cipher with 256-bit key. GOST R 34.11-94 - Message digest algorithm. 256-bit hash value. GOST R 34.10-2001 - Digital signature algorithm. GOST R 34.10-2012 - Digital signature algorithm. GOST R 34.11-2012 - "Streebog" algorithm hash functions 256 and... -
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Clean Code JavaScript
Clean Code concepts adapted for JavaScript
clean-code-javascript adapts Robert C. Martin’s Clean Code principles to the JavaScript ecosystem, presenting them as pragmatic, example-driven guidelines rather than a prescriptive style guide. It focuses on writing code that is readable, searchable, testable, and easy to refactor, using before/after (“Bad/Good”) snippets to make each idea concrete. The repository covers everyday concerns—naming, functions, conditionals, objects, classes, and error handling—showing how small choices... -
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Java Noodle Manual
The Java Face Sutra Manual consists of 5 chapters, 29 sections
Java Noodle Manual is a Java interview and core-technology study repository based on the Java Interview Manual. It uses interview questions as an entry point to explain deeper Java fundamentals instead of offering shallow memorization material. The content covers resume preparation, interview strategy, data structures, algorithms, concurrency, multithreading, JVM concepts, and source-code analysis. It includes practical examples so readers can test and verify the concepts while studying. The... -
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haskell-trainings
Haskell 101 and 102: slides and codelabs
Haskell Trainings is a collection of slides, exercises, and documentation used by Google to teach Haskell programming. It covers a wide range of topics from beginner to advanced, including functional programming principles, monads, type classes, concurrency, and performance. The repository is designed to support self-paced learning or instructor-led training and reflects Google's internal education efforts to promote functional programming skills. -
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quantitative
Quantized transactions python3
The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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Python ML Jupyter Notebooks
Practice and tutorial-style notebooks
Python ML Jupyter Notebooks is an educational repository that demonstrates how to implement machine learning algorithms and data science workflows using Python. The project provides numerous examples and tutorials covering classical machine learning techniques such as regression, classification, clustering, and dimensionality reduction. It includes code implementations that show how to build models using popular libraries like scikit-learn, NumPy, pandas, and Matplotlib. The repository is... -
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Khue's Homelab
Modern self-hosting framework, fully automated from empty disk
This project utilizes Infrastructure as Code and GitOps to automate provisioning, operating, and updating self-hosted services in my Homelab. It can be used as a highly customizable framework to build your own Homelab. Homelab is a laboratory at home where you can self-host, experiment with new technologies, practice for certifications, and so on. For more information, please see the r/homelab introduction and the Home Operations Discord community (formerly known as k8s-at-home). -
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Machine Learning Glossary
Machine learning glossary
...The content is organized into sections that progressively introduce key ideas from basic machine learning concepts to more advanced mathematical topics. Many pages include diagrams or code examples to illustrate how algorithms work in practice. Because the project emphasizes accessibility, it is particularly useful for beginners who want a conceptual overview of machine learning terminology before diving into more technical research papers. -
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CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
CoolplaySpark is a learning and practice repository designed to help users understand and work with Apache Spark. It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. -
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Tiny 84a Morse Code
Flashlight morse code for the Tiny84a
Hopefully this will help get morse code into flashlights. Seems everyone wants a light that goes high. I built these lights years ago. The buck was a personal design I had fabbed at oshpark and it fit into a modded budget light. The code should be able to be ported to other chips with changes. I picked the 84a because of it's size. There was no pic size equivalent. -
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LeetCode
LeetCode Problems' Solutions
LeetCode is a long-running repository of solutions to LeetCode programming problems. It is organized as a study and reference collection for algorithm practice, technical interview preparation, and problem-solving review. The repository includes implementations for many classic coding challenge categories such as arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and math. It is useful for comparing approaches, reviewing solution patterns, and studying how common interview problems can be implemented in code. ... -
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LeetCode Python
LeetCode Solutions: A Record of My Problem Solving Journey
This repository is a comprehensive personal journal of LeetCode problem-solving journey. It includes detailed solutions with code, algorithm insights, data structure summaries, Anki flashcards, daily challenge logs, and future planning sections. -
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Tech Interview Handbook
Curated coding interview preparation materials
Tech Interview Handbook is a curated, mostly self-contained compilation of technical interview preparation resources—including algorithms, system design, resume tips, and behavioral questions—crafted for busy software engineers. The information in this repository is condensed. Ultimately, the key to succeeding in technical interviews is consistent practice and I don't want to bore you with too many words. I tell you the minimum you need to know on how to go about navigating the interview... -
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JSettlers2 - Java Settlers of Catan
Java Settlers
JSettlers2 is a web-based version of the board game Settlers of Catan written in Java. This client-server system supports multiple simultaneous games between people and/or AI bots. Originally written by Robert S Thomas as an AI dissertation (http://sourceforge.net/projects/jsettlers). The active source code is hosted at https://github.com/jdmonin/JSettlers2 including full history; the sourceforge CVS is historical up to 2012-09-28. -
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Statistical Rethinking 2022
Statistical Rethinking course winter 2022
This repository hosts the 2022 version of the Statistical Rethinking course. It contains course materials such as R scripts, notebooks, and worked examples aligned with McElreath’s textbook. The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a... -
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CIPS-3D
3D-aware GANs based on NeRF (arXiv)
...Otherwise, if the main discriminator dominates the generator, the mirror symmetry problem will still occur. In practice, progressive training is able to guarantee this. We have trained many times from scratch. Adding an auxiliary discriminator stably solves the mirror symmetry problem. -
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Deeplearning.ai
Study notes, summaries, and auxiliary materials for deep learning
...It distills core ideas such as optimization, regularization, convolutional networks, sequence models, and practical training tricks. The explanations aim to bridge theory and practice, often connecting mathematical intuition to code-level implications. By organizing the content as “books” or structured notes, it gives students a consistent reference to revisit as models and tooling evolve. Many learners use it to supplement course videos, reinforcing concepts before implementing assignments or projects. As a consolidated guide, it reduces context-switching and helps build a durable mental model of deep learning fundamentals.
