Classification Libraries

115 Components & Libraries

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Classification Libraries

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to increase the quality of trained models. The purpose of image augmen…

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

There are options: Below shows how to build the standalone executable on macOS, Linux and Windows.

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

There are options: A few object categories and images: Below shows how to build the standalone executable on macOS, Linux and Windows.

An open-source, low-code machine learning library in Python

PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the ex…

Deep learning with satellite & aerial imagery

Extracting roads is challenging due to the occlusions caused by other objects and the complex traffic environment In instance segmentation, each individual 'instance' of a segmented area is given a u…

Python code for common Machine Learning Algorithms

Python codes for common Machine Learning Algorithms

Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

State-of-the-art Deep Learning library for Time Series and Sequences. If you plan to develop tsai yourself, or want to be on the cutting edge, you can use an editable install. First install PyTorch, …

Snips Python library to extract meaning from text

Behind every chatbot and voice assistant lies a common piece of technology: Natural Language Understanding (NLU). Anytime a user interacts with an AI using natural language, their words need to be tr…

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

You can start with this article that I wrote in Heartbeat magazine (on Medium platform): Jupyter notebooks covering a wide range of functions and operations on the topics of NumPy, Pandans, Seaborn, …

The machine learning toolkit for time series analysis in Python

There are different alternatives to install tslearn:

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

This repository contains all the code, notebooks and examples used in this book. We will also be adding bonus content here from time to time. So keep watching this space! Master the essential skills …

✨ Argilla: Open-source platform to build better language models through human feedback

Argilla Client: a powerful Python library for reading and writing data into Argilla, using all the libraries you love (transformers, spaCy, datasets, and any other). Argilla Server and UI: the API an…

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

Text analytics can be a bit overwhelming and frustrating at times with the unstructured and noisy nature of textual data and the vast amount of information available. "Text Analytics with Python" is …

MLBox is a powerful Automated Machine Learning python library.

MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone.

Multi-class confusion matrix library in Python

Fig1. ConfusionMatrix Block Diagram After that, two scores are calculated for each confusion matrices, overall and class-based. The overall score is the average of the score of seven overall benchmar…

fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.

🚀 Introducing VL Profiler! 🚀 We're excited to announce our new cloud product, VL Profiler. It's designed to help you gain deeper insights and enhance your productivity while using fastdup. With VL P…

✨ Rubrix, open-source framework for data-centric NLP. Data annotation and monitoring for enterprise NLP

Why Rubrix? Interactive weak supervision. Building a news classifier with user search queries: Getting started with Rubrix is as easy as: Then simply run: After a few iterations of data annotation, w…

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

Does one of these scenarios sounds familiar to you? If so, you are one of the people we've built refinery for. refinery helps you to build better NLP models in a data-centric approach. Semi-automate …

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy: Pyfolio is automatically instal…

Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .

All the Observers can store their state in databases (Sqlite, Postgres, MySQL, etc.), making Obsei suitable for scheduled jobs or serverless applications. Install the following (if not present alread…

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

This book brings the fundamentals of Machine Learning to you, using tools and techniques used to solve real-world problems in Computer Vision, Natural Language Processing, and Time Series analysis. T…

A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.

You can run Inference on an edge device like an NVIDIA Jetson, or on cloud computing platforms like AWS, GCP, and Azure. Currently, the stream interface only supports object detection Check out Infer…

A Python toolbox/library for reality-centric machine learning/deep learning on partially-observed time series with PyTorch, including SOTA neural network models supporting tasks of imputation, classification, clustering, and forecasting on incomplete (irregularly-sampled) multivariate time series with NaN missing values/data.

At PyPOTS, things are related to coffee, which we're familiar with. Yes, this is a coffee universe! As you can see, there is a coffee pot in the PyPOTS logo. And what else? Please read on ;-) ☕️ Welc…

Medical image processing in Python

MedPy is an image processing library and collection of scripts targeted towards medical (i.e. high dimensional) image processing.

Tensorflow based training and classification scripts for text, images, etc

This repository contains code to: setting up tensorflow classifier and retraining it find the tutorials here:

Awesome Projects in Python - Machine Learning Applications, Games, Desktop Applications all in Python :snake:

This repository contains a curated list of some of the awesome small projects made in Python that you can code away this summer. It includes analysis of different Python modules, a deep analysis of t…

This repository consists of all my Machine Learning Projects.

Machine Learning notebooks for refreshing concepts.

Helpful jupyter noteboks that I compiled while learning Machine Learning and Deep Learning from various sources on the Internet. Linear & Multiple Regression Logistic Regression Regularization

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