Jupyter Libraries

103 Components & Libraries

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Jupyter Libraries

AutoML Web App - build Machine Learning pipeline in automatic way with Graphical User Interface (GUI). You can run app locally!

This is a Web Application designed to train Machine Learning pipelines using MLJAR AutoML, specifically tailored for tabular data. All the generated models are compressed into an archive format, allo…

Custom Jupyter widgets for creating interactive 2D/3D maps using popular JavaScript libraries with bidirectional communication, such as Cesium, Mapbox, MapLibre, Leaflet, and OpenLayers

A python project starter template for data-analytics and data-science.

A project template to quick start data analytics and machine learning task. You can connect with me here:

《Python 数学建模算法与应用》- 司守奎，知识点笔记 & 代码 (Python Mathematical Modeling)

《Python 数学建模算法与应用》知识点与代码，按章节整理基于书籍内容完成，内容清晰，代码可运行，欢迎 Star 如果你希望

Template Para a Python Week 2002 - 25 a 29 de Abril na LINUXTips

Template Para a Python Week 2022 - 25 a 29 de Abril na Linux Tips No replit.com o poetry já está disponível e no gitpod será instalado assim que o ambiente iniciar. O comando a seguir instala as depe…

Open Dataset of Cobalt Strike Beacon metadata (2018-2022)

To overcome the filesize limit of 100mb on GitHub, the dataset is split by year as: We recommend using Pandas to load the dataset. Example to load a single year: Or to load everything as one big Data…

A Pure Python, React-style Framework for Scaling Your Jupyter and Web Apps

While there are many Python web frameworks out there, most are designed for small data apps or use paradigms unproven for larger scale. Code organization, reusability, and state tend to suffer as app…

Detecting silent model failure. NannyML estimates performance for regression and classification models using tabular data. It alerts you when and why it changed. It is the only open-source library capable of fully capturing the impact of data drift on performance.

Because NannyML can estimate performance, it is possible to weed out data drift alerts that do not impact expected performance, combatting alert fatigue. Besides linking data drift issues to drops in…

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling you to thoroughly test your data and models from research to production. Deepchecks includes: For …

JupyterLab client for Tabnine. https://pypi.org/project/jupyterlab-tabnine/

Tabnine delivers three times the AI for better collaboration, better privacy protection, and better code completion. Reduce development costs, eliminate unnecessary QA-ing, and deliver final code fas…

Get started with Machine Learning with Python - An introduction with Python programming examples

There are two options. Note: On each of those options, you'll find: No installations needed. Note: On each notebook, click on "Open in Colab", in order to open it on Google Colab Worried about whethe…

A Jupyter server based on FastAPI :rocket:

Try it online:

This repository contains all the DSA (Data-Structures, Algorithms, 450 DSA by Love Babbar Bhaiya, FAANG Questions), Technical Subjects (OS + DBMS + SQL + CN + OOPs) Theory+Questions, FAANG Interview questions, and Miscellaneous Stuff (Programming MCQs, Puzzles, Aptitude, Reasoning). The Programming languages used for demonstration are C++, Python, and Java.

We'd love your contributions! Kindly follow the steps below to get started: Clone the forked repository. Make changes. Stage your changes and commit

Beautifully colored, quick and simple Python logging

Objectiv is open-source product analytics infrastructure with a generic event taxonomy.

Self-hosted, 100% free to use and fully open source. Supports a wide range of product analytics use cases. We're currently working on extending the range of marketing related use cases. Objectiv curr…

Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data science models and products with a focus on geospatial data. Currently, the following data connectors are available worldwide: a) High-resolution demographics data b) Point of Interests from Open Street Map c) Google Popular Times

Currently we support the following databases and data warehouses For connecting and loading all your tooling data into a data warehouse, we are integrating with Airbyte connectors. For everything rel…

Beginner Python Course with JuPyter Notebooks. Includes 17 video tutorials, 17 lessons, 17 projects, with 17 solutions.

There are two options. Note: On each of those options, you'll find: No installations needed. Note: On each notebook, click on "Open in Colab", in order to open it on Google Colab

A collection of Digital Signal Processing notebooks with a wireless communications theme.

Once installation has complete you will find the DSP notebooks in the Jupyter workspace directory 'rfsoc-studio/dsp-notebooks'. The folder will be named 'dsp-notebooks'.

Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment

This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach.

Recent advances in Machine Learning are pushing the boundaries of real world AI applicationsand are becoming more and more integrated in our daily lives. As researchadvances, the long-term goal of au…

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning

My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

Datasets drive vision progress, yet existing driving datasets are limited in terms of visual content, scene variation, the richness of annotations, and the geographic distribution and supported tasks…

Lectures on Computational Communication

Elements of Computational Communication 王成军需要声明的是，本在线书籍中不少应用内容来源于多本其它重要书籍，并非笔者独创。因本书内容驳杂，而个人能力所限，难免存在诸多谬误；对于其中涉及的错误，笔者皆愿意承担。

Welcome to Machine Learning: Zero to Hero: From the fundamentals of machine learning to advanced techniques like regressions, classification, clustering, Neural Networks, OpenCV, Recommendation Engines and more, this Python-based repository provides a comprehensive guide for mastering ML.

This project was originally initiated under the influence of Google Developer Student Clubs and Microsoft Learn Student Ambassadors - SSUET campus to teach more and more students about technology. Ov…

A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.

(aka the "awesome-notebooks") The objective of this repository is to create the largest catalog of production-ready Jupyter Notebooks templates. With those templates, it becomes easy to create data p…

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

Being specialized in domains like computer vision and natural language processing is no longer a luxury but a necessity which is expected of any data scientist in today’s fast-paced world! With a han…

Introduction to Cultural Analytics & Python, course website and online textbook powered by Jupyter Book

The book demonstrates how Python can be used to study cultural materials such as song lyrics, short stories, newspaper articles, tweets, Reddit posts, and film screenplays. It also introduces computa…

(Still exploring) My cryptography journey: A collection of notebooks covering different algorithms and concepts from cryptography

In this repository I collect my adventures in the Cryptography world. What to expect? Directories are organized by categories (S = Symmetric, P = Public, E = Extra) Each directory will have a README.…

Scientific Computing for Chemists text for teaching basic computing skills to chemistry students using Python, Jupyter notebooks, and the SciPy stack. This text makes use of a variety of packages including NumPy, SciPy, matplotlib, pandas, seaborn, NMRglue, SymPy, scikit-image, and scikit-learn.

The following is the textbook used for the Scientific Computing Chemists course intended to teach chemists and chemistry students basic computer programming in Python and Jupyter Notebooks and advanc…

Pyscript adds rich Python scripting to HASS

This HACS custom integration allows you to write Python functions and scripts that can implement a wide range of automation, logic and triggers. State variables are bound to Python variables and serv…

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