Search Results for "dynamicreports-examples" - Page 23
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Showing 799 open source projects for "dynamicreports-examples"
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AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations. It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose)... -
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Reinforcement Learning Methods
Simple Reinforcement learning tutorials
Reinforcement-Learning-with-TensorFlow is an educational repository that walks through key reinforcement learning algorithms implemented in TensorFlow. It provides clear code examples for foundational techniques like Q-learning, policy gradients, deep Q-networks, actor-critic methods, and value function approximation within familiar simulation environments. Each algorithm is structured with readable code, explanatory comments, and corresponding environment interaction loops so learners can easily trace how actions, rewards, and model updates connect. ... -
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VSCode-LaTeX-Inkscape
A way to integrate LaTeX, VS Code, and Inkscape in macOS
A way to integrate LaTeX, VS Code, and Inkscape in macOS. I use LaTeX heavily for both academic work and professional work, and I think I'm quite proficient in terms of typing things out in LaTeX. But when I see the mind-blowing blog posts from Gilles Castel (RIP)-How I'm able to take notes in mathematics lectures using LaTeX and Vim and also How I draw figures for my mathematical lecture notes using Inkscape, I realize that I'm still far from fast, so I decided to adapt the whole setup from... -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time... -
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Bloxs
Build dashboards in Jupyter Notebook with numeric and chart boxes
Bloxs is a simple Python package that helps you display information in an attractive way (formed in blocks). Perfect for building dashboards, reports and apps in the notebook. -
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
Soft sensors have continued growing interest in robotics, due to their ability to enable both passive conformal contact from the material properties and active contact data from the sensor properties. However, the same properties of conformal contact result in faster deterioration of soft sensors and larger variations in their response characteristics over time and across samples, inhibiting their ability to be long-lasting and replaceable. ReSkin is a tactile soft sensor that leverages... -
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pyntcloud
pyntcloud is a Python library for working with 3D point clouds
This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and... -
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Machine Learning Glossary
Machine learning glossary
...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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mlscraper
ML-based HTML scraper that learns extraction rules from examples
mlscraper is a Python library designed to automatically extract structured data from HTML pages without requiring developers to manually write CSS selectors or XPath rules. Instead of defining extraction logic by hand, users provide a few examples of the data they want to retrieve from a webpage. It analyzes those examples within the HTML document and determines patterns or rules that can be used to extract the same type of information from similar pages. Once trained, the generated scraper can process new pages and return the extracted data in structured formats such as dictionaries or lists. ... -
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nlpaug
Data augmentation for NLP
This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together. -
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Crunch PNG
Insane(ly slow but wicked good) PNG image optimization
Crunch is a tool for lossy PNG image file optimization. It combines selective bit depth, color type, and color palette reduction with zopfli DEFLATE compression algorithm encoding using the pngquant and zopflipng PNG optimization tools. This approach leads to a significant file size gain relative to lossless approaches at the expense of a relatively modest decrease in image quality. Continuous benchmark testing is available in our GitHub Actions CI. Please see the benchmarks directory of... -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
...It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. YOLOv7 introduced training-time improvements that raise accuracy without increasing inference cost, which is why the project became important in real-time detection research. It supports multiple model sizes and related tasks such as object detection and instance segmentation through associated branches or weights. ... -
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G2SConverter
Convert models from GoldSource engine to Source engine with AI
...An example of a processed texture is shown in the following image (parameters used: scaling-factor = 4 and deblur iterations = 4) besides upscaling and debluring the utility also generates normal maps for each texture. This is implemented using the DeepBump by HugoTiny model. Examples of normal maps are shown in the following images. -
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RoBERTa for Chinese
RoBERTa Chinese pre-training model: RoBERTa for Chinese
...Its training data includes news, community discussion, encyclopedia content, and other broad Chinese text sources. The repository also describes whole word masking for Chinese and provides examples for loading and fine-tuning models on sentence-pair matching tasks. Overall, it is a useful pretrained model resource for developers who want stronger Chinese BERT-style representations for classification, matching, reading comprehension, and related NLP tasks. -
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100+ Python Projects Challenge
100+ Python Projects Challenge
...This makes it useful for users who want to build a portfolio of small programs while reinforcing programming fundamentals. The repository is aimed at learners who benefit from doing, modifying, and expanding examples. It is best used as a progressive challenge list for turning Python knowledge into visible working projects. -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
...Although the repository has been marked as deprecated in favor of language-specific repositories for new work, it still serves as a broad reference hub for legacy examples and multi-language implementation patterns. -
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LaTeX Cookbook
A comprehensive LaTeX template with examples for theses, books, etc.
This repo contains a LaTeX document, usable as a cookbook (different "recipes" to achieve various things in LaTeX) as well as a template. The resulting PDF covers LaTeX-specific topics and instructions on compiling the LaTeX source. -
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pyTorch Tutorials
Build your neural network easy and fast
...Each example explains PyTorch’s dynamic computation graph, optimization techniques, and core abstractions in a way that is accessible and reproducible. Contributors and authors integrate visual and coded examples so readers can see both the theory and the implementation side-by-side. -
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Whisper Library
Whisper is a file-based time-series database format for Graphite
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target... -
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PromptSource
Toolkit for creating, sharing and using natural language prompts
PromptSource is a toolkit for creating, sharing and using natural language prompts. Recent work has shown that large language models exhibit the ability to perform reasonable zero-shot generalization to new tasks. For instance, GPT-3 demonstrated that large language models have strong zero- and few-shot abilities. FLAN and T0 then demonstrated that pre-trained language models fine-tuned in a massively multitask fashion yield even stronger zero-shot performance. A common denominator in these... -
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castero
TUI podcast client for the terminal
castero is a TUI podcast client for the terminal. -
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Texar-PyTorch
Integrating the Best of TF into PyTorch, for Machine Learning
Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar-PyTorch was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror... -
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Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
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Fashion-MNIST
A MNIST-like fashion product database
...It was designed as a direct replacement for the original MNIST handwritten digits dataset, maintaining the same structure and image size so that researchers could easily switch datasets without modifying their experimental pipelines. The dataset consists of 70,000 images in total, with 60,000 examples used for training and 10,000 reserved for testing. Each image has a resolution of 28 by 28 pixels and belongs to one of ten clothing classes, making it suitable for evaluating classification models. Because the dataset represents real-world objects rather than handwritten digits, it offers a more challenging benchmark for testing machine learning algorithms. -
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bert4keras
Keras implement of transformers for humans
Our light reimplementation of bert for keras. A cleaner, lighter version of bert for keras. This is the keras version of the transformer model library re-implemented by the author and is committed to combining transformer and keras with as clean code as possible. The original intention of this project is for the convenience of modification and customization, so it may be updated frequently. Load the pre-trained weights of bert/roberta/albert for fine-tune. Implement the attention mask...