Search Results for "dynamicreports-examples" - Page 22
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Showing 659 open source projects for "dynamicreports-examples"
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BitTiger
Lifelong Learning University from Silicon Valley
...The project reflects the philosophy of a “lifelong learning university,” aiming to help learners bridge the gap between academic knowledge and industry skills by exploring applied concepts across multiple domains. It includes structured modules on algorithms, system design, and emerging technologies, along with hands-on examples such as blockchain implementations and AI experiments. -
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Keras TCN
Keras Temporal Convolutional Network
...The receptive field of the TCN can be calculated. Once keras-tcn is installed as a package, you can take a glimpse of what is possible to do with TCNs. Some tasks examples are available in the repository for this purpose. -
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ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,... -
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Objectron
A dataset of short, object-centric video clips
The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists... -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
Welcome to Amazon SageMaker. This projects highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker. If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies... -
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Semantic Segmentation Editor
Web labeling tool for bitmap images and point clouds
A web-based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js, and three.js. -
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Bayesian machine learning notebooks
Notebooks about Bayesian methods for machine learning
Notebooks about Bayesian methods for machine learning. -
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TensorLayer
Deep learning and reinforcement learning library for scientists
...TensorLayer has a high-level layer/model abstraction which is effortless to learn. You can learn how deep learning can benefit your AI tasks in minutes through the massive examples. -
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transferlearning-tutorial
Tutorial on applied transfer learning
A bilingual (English/Chinese) concise tutorial on applied transfer learning, hosted by Jindong Wang. It includes LaTeX source for a compact handbook covering theory, algorithms, surveys, and code in MATLAB and Python. -
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Cloud Annotations
A fast, easy and collaborative open source image annotation tool
...Learn to build and train computer vision models—then show off your skills in an interactive web application. Build impressive applications and learn coveted skills. The examples below were created by the Skills Network Team—right here in CV Studio. Create your own project dataset by uploading images and videos. Coming soon, you'll be able to use a pre-compiled dataset so you can hit the ground running. Creating image annotations for your project is easy inside CV Studio. For classification projects, just select and label your images. ... -
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Rust Telegram Bot Library
Rust Library for creating a Telegram Bot
A library for writing your own Telegram bots. -
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DeepMind Lab
A customizable 3D platform for agent-based AI research
...To enable compiler optimizations, pass the flag --compilation_mode=opt, or -c opt for short, to each bazel build, bazel test and bazel run command. The flag is omitted from the examples here for brevity, but it should be used for real training and evaluation where performance matters. DeepMind Lab ships with an example random agent in python/random_agent.py which can be used as a starting point for implementing a learning agent. -
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Libra
Ergonomic machine learning for everyone
An ergonomic machine learning library for non-technical users. Save time. Blaze through ML. -
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
...It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. ... -
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Effective TensorFlow 2
TensorFlow tutorials and best practices
...It includes practical guidelines that explain common pitfalls in neural network training, such as numerical instability and gradient-related issues. The repository also demonstrates techniques for improving model performance, optimizing training loops, and debugging TensorFlow programs. Through examples and explanations, the project highlights how developers can structure machine learning code to improve readability and maintainability. The tutorials emphasize both conceptual understanding and implementation details so that users can build more robust deep learning systems. -
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TensorFlow 2.0 Tutorials
TensorFlow 2.x version's Tutorials and Examples
TensorFlow 2.0 Tutorials is an open-source educational repository that provides practical examples and walkthroughs for learning deep learning using the TensorFlow 2.x framework. The repository contains a large set of hands-on tutorials that demonstrate how to build neural networks and machine learning systems with modern TensorFlow APIs. These examples cover a wide range of topics including convolutional neural networks, recurrent neural networks, generative adversarial networks, autoencoders, and transformer-based models such as GPT and BERT. ... -
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flowerss bot
A telegram bot for RSS reader
A telegram bot for RSS readers. A Telegram RSS Bot that supports reading in the application. -
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HyperGAN
Composable GAN framework with api and user interface
...Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with the 2d-distribution.py. Check out random_search.py for possibilities, you'll likely want to modify it. The examples are capable of (sometimes) finding a good trainer, like 2d-distribution. Mixing and matching components seems to work. -
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Computer Vision
Best Practices, code samples, and documentation for Computer Vision
...A key part to many of these applications are visual recognition tasks such as image classification, object detection and image similarity. This repository provides examples and best practice guidelines for building computer vision systems. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in Computer Vision algorithms, neural architectures, and operationalizing such systems. Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utility around loading image data, optimizing and evaluating models, and scaling up to the cloud. -
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GluonNLP
NLP made easy
...To facilitate both the engineers and researchers, we provide command-line-toolkits for downloading and processing the NLP datasets. Gluon NLP makes it easy to evaluate and train word embeddings. Here are examples to evaluate the pre-trained embeddings included in the Gluon NLP toolkit as well as example scripts for training embeddings on custom datasets. Fasttext models trained with the library of Facebook research are exported both in text and a binary format. Unlike the text format, the binary format preserves information about subword units and consequently supports the computation of word vectors for words unknown during training (and not included in the text format). ... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...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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NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional models for text processing, and transformer-style attention mechanisms. ... -
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Ad Generator
Professional text randomizer and ad generator by Airat Khalitov
Professional text randomizer and ad generator by Airat Khalitov / Professional text randomizer and ad generator. Author: Airat Halitov. Visit 'Plugins, Add New', click 'Upload Plugin', upload the file 'ad-generator.zip', and activate Ad Generator from your Plugins page. Add [ad_generator] shortcode to WordPress Page. Create a new WordPress Page, add [ad_generator] shortcode and save. Go to the page and use the ad generator. This is a program for industrial creation of pseudo-unique content.... -
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TrashEmail
A hosted disposable email telegram bot; Extremely privacy friendly
TrashEmail is a hosted Telegram bot that can save your private email address by offering a disposable email address. It can create, and manage, disposable email addresses and link them with your telegram bot chat. -
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TransmogrifAI
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library written in Scala that runs on top of Apache Spark. It was developed with a focus on accelerating machine learning developer productivity through machine learning automation, and an API that enforces compile-time type-safety, modularity, and reuse. Through automation, it achieves accuracies close to hand-tuned models with almost 100x reduction in time.
