Search Results for "scratch" - Page 4
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Showing 122 open source projects for "scratch"
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Music Source Separation
Separate audio recordings into individual sources
Music Source Separation is a PyTorch-based open-source implementation for the task of separating a music (or audio) recording into its constituent sources — for example isolating vocals, instruments, bass, accompaniment, or background from a mixed track. It aims to give users the ability to take any existing song and decompose it into separate stems (vocals, accompaniment, etc.), or to train custom separation models on their own datasets (e.g. for speech enhancement, instrument isolation, or... -
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Neuro-comma
Punctuation restoration production-ready model for Russian language
This library was developed with the idea to help us to create punctuation restoration models to memorize trained parameters, data, training visualization, etc. The Library doesn't use any high-level frameworks, such as PyTorch-lightning or Keras, to reduce the level entry threshold. Feel free to fork this repo and edit model or dataset classes for your purposes. Our team always uses the latest version and features of Python. We started with Python 3.9, but realized, that there is no FastAPI... -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying solely on black-box frameworks. This makes the repo suitable for students, hobbyists, or developers who want to deeply understand how ML algorithms work under the hood and experiment with parameter tuning or custom data. Because it's part of the author’s learning-path repositories, it likely is integrated with tutorials, sample datasets, and contextual guidance, which helps users bridge theory. -
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Footcontroller
Control your Linux PC with a standard foot pedal
...The advantage is that now, your foot pedal can perform different tasks in multiple situations simply by selecting the appropriate pedal set, rather than having to re-program the foot pedal from scratch. -
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
...BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end. We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, backend servers etc., that are simply not within the scope of a typical data scientist. BudgetML is our answer to this challenge. It is supposed to be fast, easy, and developer-friendly. It is by no means meant to be used in a full-fledged production-ready setup. ... -
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PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
...Aside from a few tricks when performing fine-tuning (if the case), it has been shown (many times) that if training for a new task, models initialized with pre-trained weights tend to learn faster and be more accurate then training from scratch using random initialization. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions. -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
...It constructs a dynamic computation graph as you perform math operations and then computes gradients by walking that graph backward, making it an approachable “from scratch” autograd reference. On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple models with a PyTorch-like feel, including multilayer perceptrons. The repository is intentionally compact and readable, prioritizing clarity over performance so learners can follow every step of gradient flow and parameter updates. ... -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
ML-From-Scratch is an open-source machine learning project that demonstrates how to implement common machine learning algorithms using only basic Python and NumPy rather than relying on high-level frameworks. The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. -
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Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2... -
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Full Stack FastAPI Couchbase
Full stack, modern web application generator
...REST backend tests based on Pytest, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time (so you can use ElasticSearch, MongoDB, or whatever you want, and just test that the API works). Load balancing between frontend and backend with Traefik, so you can have both under the same domain, separated by path, but served by different containers. -
12
myHouse
Home monitoring and automation suite now known as eGeoffrey
...If you want to give it a look, check out https://www.egeoffrey.com. I've also put together a migration utility to help along to way in case you want to move into the new platform without starting from scratch: https://github.com/myhouse-project/myHouse2eGeoffrey myHouse itself will be no longer maintained since the new eGeoffrey offers the same functionalities and many more. Thanks for your support along the way! -
13
SSD Keras
A Keras port of single shot MultiBox detector
...Ports of the trained weights of all the original models are provided below. This implementation is accurate, meaning that both the ported weights and models trained from scratch produce the same mAP values as the respective models of the original Caffe implementation. The main goal of this project is to create an SSD implementation that is well documented for those who are interested in a low-level understanding of the model. The provided tutorials, documentation and detailed comments hopefully make it a bit easier to dig into the code and adapt or build upon the model than with most other implementations out there (Keras or otherwise) that provide little to no documentation and comments. ... -
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pyhanlp
Chinese participle
...It is especially useful when you need a pragmatic “get results quickly” NLP layer for segmentation, tagging, entity extraction, parsing, or keyword-style tasks rather than experimenting with model training from scratch. -
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Retrieval-Based Conversational Model
Dual LSTM Encoder for Dialog Response Generation
Retrieval-Based Conversational Model in Tensorflow is a project implementing a retrieval-based conversational model using a dual LSTM encoder architecture in TensorFlow, illustrating how neural networks can be trained to select appropriate responses from a fixed set of candidate replies rather than generate them from scratch. The core idea is to embed both the conversation context and potential replies into vector representations, then score how well each candidate fits the current dialogue, choosing the best match accordingly. Designed to work with datasets like the Ubuntu Dialogue Corpus, this codebase includes data preparation, model training, and evaluation components for building and assessing dialog models that can handle multi-turn conversations. -
16
MITMf
Framework for Man-In-The-Middle attacks
MITMf aims to provide a one-stop-shop for Man-In-The-Middle and network attacks while updating and improving existing attacks and techniques. Originally built to address the significant shortcomings of other tools (e.g Ettercap, Mallory), it's been almost completely rewritten from scratch to provide a modular and easily extendible framework that anyone can use to implement their own MITM attack. The framework contains a built-in SMB, HTTP and DNS server that can be controlled and used by the various plugins, it also contains a modified version of the SSLStrip proxy that allows for HTTP modification and a partial HSTS bypass. ... -
17
Python Programming in iPhone
Learn Python Programming and Scripting using your iPhone
...This tutorial gives enough understanding on Python programming language. Audience This tutorial is designed for software programmers who need to learn Python programming language from scratch. Prerequisites You should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages is a plus. -
18
Little Server That Can
LSTC is a plugin server in Python.
LSTC is designed for the use of a server for Scratch (http://scratch.mit.edu/). It's also designed in a way that you can connect to different "plugins" allowing one person to play chat and another to play a multiplayer game without either of the projects interfering with the other. With a little modification (of the parsing and sending messages), you can use it with raw sockets for other projects made outside of Scratch. -
19
RainforestCluster
Dynamically manage Amazon EC2 clusters
...It is also able to optimize the use of spot instances - idle computers in Amazon's cloud that are available at drastically reduced cost (5x-10x cheaper) - but can be terminated at any moment if capacity drops or the bid price rises. It also provides pre-installed features such as GlusterFS distributed filesystems, ThunderstormDistributor queuing system, RAID 0 /scratch, password-less ssh, and automatic cluster management, for ease of use and maximum processing speed for computational tools. Originally it was developed as a different version for the Wall Lab at Harvard CBMI. -
20
grandPA
DMX Software,Lichtsteuerung,Moving Light,LED,ArtNet DMX,
...) - Programmer (pygame,tkinter,curses ) - per Midi/RS232/USB steuerbar [1] Teilweise - UI / GUI (schnell Spiele GUI als oberfläche) - Lauflicht Stack (Chaser) ToDo - Cue's - Sequenzen - code redesign (modularer) - mini Linux als Basis (LFS Linux from Scratch) - Multiuser / Multiprogrammer https://www.youtube.com/watch?feature=player_embedded&v=v5mJw2MNEHQ&noredirect=1 [1] jede hardware bekommt eigenes kleines software modul mit eigener logik neue Seite: https://sourceforge.net/projects/librelight/ -
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M30W
M30W is a program designed to help create Scratch projects quickly.
M30W is a program designed to allow fast developing of Scratch projects. It uses a unique text syntax to allow typing of blocks rather than laggy dragging them around. -
22
microhex [discontinued]
Crossplatform hex-editing software based on Python and Qt
This project is no longer supported. Use it on your own risk (or not use at all). Microhex is an intuitive HEX editing application that enables you to view and manipulate binary data for any file in your computer. Microhex displays the integer column and the characters column, allowing you to add new columns and delete existing ones. Each column can be assigned an unlimited number of linked address bars. -
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gtkodos
A python regex testing tool
Gtkodos is a python regex testing tool. It represents a clone of Kodos written using the Gtk3 libraries. The code has been rewritten from scratch. -
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PyProperties
Provides support for properties files in Python 3.x
pyproperties provides support for properties files in Python. Being written entirely from scratch it is not in any way derived from java.util.Properties. There are projects which try to mimic j.u.P. This is not one of them. It can read, parse and store properties files but also provides some more advanced functionality like manipulating comments and type-guessing. -
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Lightning Planning Framework for ROS
ROS package implementing the Lightning Framework using OMPL
...For later ROS versions, see https://github.com/WPI-ARC/lightning_ros This approach uses a path library to store previous experience while allowing generality by also planning from scratch. Please see the paper below for more details: A Robot Path Planning Framework that Learns from Experience Dmitry Berenson, Pieter Abbeel, and Ken Goldberg IEEE International Conference on Robotics and Automation (ICRA), May, 2012. This package uses OMPL planners (http://ompl.kavrakilab.org/) to implement each component in lightning and can be called the same way as any other OMPL planner. ...
