Search Results for "google-visualization-python" - Page 29
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Showing 1024 open source projects for "google-visualization-python"
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1
Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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Advanced RecyclerView
RecyclerView extension library which provides advanced features
This RecyclerView extension library provides Google's Inbox app like swiping, Play Music app like drag-and-drop sorting and expandable item features. Works on API level 14 or later. Reduces library conflicts, easy to integrate with existing code. Looks difficult at a glance, but gives great flexibility like the original RecyclerView. Swipe dismiss and swipe pinning operation. (like Google's Inbox app). Smooth item reordering with linear list (LinearLayoutManager). It behaves like the... -
3
PlotNeuralNet
Latex code for making neural networks diagrams
Latex code for drawing neural networks for reports and presentations. Have a look into examples to see how they are made. Additionally, let's consolidate any improvements that you make and fix any bugs to help more people with this code. -
4
ComplexEventExtraction
Expression pattern collection of Chinese compound event extraction
ComplexEventExtraction is a Chinese NLP project for identifying relationships between events expressed in compound sentences. It defines patterns for causal, conditional, sequential, contrastive, and parallel event structures. The system uses explicit connective words and phrase combinations to split text into linked event pairs. Extracted results can support event graphs that represent how situations develop, conflict, or depend on one another. The repository catalogs hundreds of linguistic... -
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5
FilterPy
Python Kalman filtering and optimal estimation library
...NumPy and SciPy handle the numerical work, with Matplotlib commonly used for visualization. The library accompanies the book Kalman and Bayesian Filters in Python and is useful for learning, prototyping, tracking, navigation, and estimation experiments. -
6
Autologging
Easier logging and tracing of Python functions and class methods.
..."autologging.traced" decorates a class to provide automatic CALL/RETURN tracing for all class, static, and instance methods, as well as the special __init__ method (by default) "autologging.TRACE" is a custom log level (lower than logging.DEBUG) that is registered with the Python logging module when autologging is imported -
7
Teach Me Quantum
Practical Course on Quantum Information Science and Quantum Computing
A university-level course on Quantum Computing and Quantum Information Science that incorporates IBM Q Experience and Qiskit. This course is adequate for general audiences without prior knowledge on Quantum Mechanics and Quantum Computing (see prior knowledge), has an estimated average duration of 10 weeks at 3h/week (see duration), and is meant to be the entrypoint into the Quantum World. -
8
WIP
Create Siri Shortcuts with Python
python-shortcuts is a library to create Siri Shortcuts on your laptop with your favorite text editor. It uses toml to represent shortcuts. The library is in a very early development state (PR welcome!), so it does not support all actions from the Shortcuts app. -
9
SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
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10
Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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Plotly.jl
A Julia interface to the plot.ly plotting library and cloud services
A Julia interface to the plot.ly plotting library and cloud services. Plotting functions provided by this package are identical to PlotlyJS. Please consult its documentation. In fact, the package depends on PlotlyJS.jl and reexports all the methods. -
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Skater
Python library for model interpretation/explanations
Skater is a unified framework to enable Model Interpretation for all forms of the model to help one build an Interpretable machine learning system often needed for real-world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open-source python library designed to demystify the learned structures of a black box model both globally(inference on the basis of a complete data set) and locally(inference about an individual prediction). The concept of model interpretability in the field of machine learning is still new, largely subjective, and, at times, controversial. Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in algorithmic decision-making. ... -
13
Ponder
C++ reflection library with Lua binding, and JSON and XML
...For example, Ponder can be used to expose and edit objects' attributes in a graphical user interface. It can also be used to do automatic binding of C++ classes to script languages such as Python or Lua. Another possible application would be the serialization of objects to XML, text or binary formats. Or you can even combine all these examples to provide a powerful and consistent interface for manipulating your objects outside C++ code. -
14
Mixup-CIFAR10
mixup: Beyond Empirical Risk Minimization
mixup-cifar10 is the official PyTorch implementation of “mixup: Beyond Empirical Risk Minimization” (Zhang et al., ICLR 2018), a foundational paper introducing mixup, a simple yet powerful data augmentation technique for training deep neural networks. The core idea of mixup is to generate synthetic training examples by taking convex combinations of pairs of input samples and their labels. By interpolating both data and labels, the model learns smoother decision boundaries and becomes more... -
15
Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda management system. ... -
16
Instacapture 2.0
Android library to capture screenshot from your app
Android library to capture screenshots from your app. -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
18
Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With... -
19
easytrader
Python toolkit for automating and integrating stock trading
easytrader is a Python toolkit for automating and integrating quantitative stock trading workflows in the Chinese market. It can control supported desktop trading clients and also work with official MiniQMT interfaces. The project supports Xueqiu portfolio operations and can track simulated strategies from platforms such as JoinQuant and RiceQuant. Remote operation mode lets trading functions be exposed outside the local client environment. -
20
tkFontChooser
Simple font chooser dialog for tkinter
A simple font chooser for Tkinter that allow the user to select the font family among the fonts available on his/her system. The size and style (bold, italic, underline, strikethrough) of the text can be set too. This module contains a `FontChooser` class which implements the font chooser and an `askfont` function that displays the font chooser and returns the chosen font when the user closes the font chooser. The font is returned as a dictionary like the one returned by the... -
21
Aglyph
Aglyph is a Dependency Injection framework for Python.
...Aglyph can be configured using a declarative XML syntax, or programmatically in pure Python using a fluent API. -
22
Incanter
Clojure-based, R-like statistical computing and graphics environment
Incanter is a Clojure-based, R-like statistical computing and visualization library running on the JVM. It integrates core numerical libraries like Parallel Colt and JFreeChart to deliver data manipulation, modeling, statistical tests, and charting in a REPL-friendly environment. Start by visiting the Incanter website for an overview, check out the documentation page for a listing of HOW-TOs and examples, and then download either an Incanter executable or a pre-built version of the latest build of Incanter, which includes all the necessary dependencies, and unpack the file (if you would like to build it from source, read Building Incanter). ... -
23
easyquotation
Get free stock quotes in real time, supporting Sina
easyquotation is a lightweight Python library for retrieving Chinese stock-market data from free public quotation sources. It supports market feeds from Sina and Tencent as well as selected data from Jisilu. Developers can request complete market snapshots or query specific Shanghai, Shenzhen, Beijing, and Hong Kong securities. Returned records include prices, bid and ask data, volume, turnover, highs, lows, and other trading fields when available. -
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AlfredWorkflow.com
A public Collection of Alfred Workflows
AlfredWorkflow.com is a public collection of workflows created for Alfred 2 on macOS. It was designed to help users search, install, share, and discover automations without building each workflow from scratch. The repository contains hundreds of downloadable workflows alongside source code that developers can study. A Workflow Searcher lets users query the collection directly from Alfred. The project also exposes workflow metadata through a JSON API for programmatic access. GitHub-hosted... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates...