Search Results for "machine learning platform" - Page 33
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Showing 1058 open source projects for "machine learning platform"
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Python Tutorials
Machine Learning Tutorials
...This includes foundational Python concepts, data processing with libraries like NumPy and pandas, threading and multiprocessing for concurrency, and practical use of libraries such as Matplotlib for data visualization. It also provides tutorials on machine learning frameworks and concepts, including TensorFlow, PyTorch, Keras, Scikit-Learn, and reinforcement learning techniques. Each section contains organized code and explanations designed to help learners understand the underlying mechanics of Python and common computational approaches. -
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a... -
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GIMP ML
AI for GNU Image Manipulation Program
This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on... -
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Neural Networks Collection
Neural Networks Collection
This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people. -
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Tensorflow 2017 Tutorials
Tensorflow tutorial from basic to hard
...This repository covers essential building blocks like sessions (for older TF versions), placeholders, variables, activation functions, and optimizers, before guiding learners through building end-to-end models for regression, classification, and data pipelines. Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. By pairing code examples with conceptual explanations, the tutorials make abstract machine learning ideas accessible and encourage experimentation with TensorBoard visualization and distributed training. -
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models... -
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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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surpriver
Find big moving stocks before they move using machine learning
surpriver is a machine learning project designed to identify unusual stock market activity that may precede large price movements. The system analyzes historical stock price and volume data to detect anomalies that could indicate potential trading opportunities. By applying machine learning techniques to market indicators, the tool attempts to identify patterns in trading behavior that deviate significantly from normal market activity. -
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PyArmadillo
linear algebra library for Python
PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma -
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SQLFlow
SQL compiler bridging databases and machine learning workflows
SQLFlow is an open source project designed to bridge the gap between traditional SQL-based data processing and modern machine learning workflows by extending SQL syntax with AI capabilities. It acts as a compiler that translates SQL programs into executable workflows, enabling users to train, evaluate, and deploy machine learning models directly from SQL statements. It integrates with multiple database engines such as MySQL, Hive, and MaxCompute, while also supporting machine learning frameworks like TensorFlow and XGBoost. ... -
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Eiten
Statistical and Algorithmic Investing Strategies for Everyone
Eiten is an open-source Python project focused on providing statistical and algorithmic trading strategies powered by data analysis and machine learning techniques. It is designed to make quantitative investing more accessible by offering ready-to-use strategies that analyze market behavior, detect patterns, and generate actionable insights. The project includes tools for evaluating stock performance, identifying trends, and applying algorithmic models to financial data, enabling users to experiment with different investment approaches. ... -
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EfficientNet Keras
Implementation of EfficientNet model. Keras and TensorFlow Keras
This repository contains a Keras (and TensorFlow Keras) reimplementation of EfficientNet, a lightweight convolutional neural network architecture achieving state-of-the-art accuracy with an order of magnitude fewer parameters and FLOPS, on both ImageNet and five other commonly used transfer learning datasets. Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we... -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. ... -
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Stable Baselines
A fork of OpenAI Baselines, implementations of reinforcement learning
Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a detailed presentation of Stable Baselines in the Medium article. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around which new ideas can be added, and as a tool for comparing a new... -
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Delta ML
Deep learning based natural language and speech processing platform
DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. -
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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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MMdnn
Tools to help users inter-operate among deep learning frameworks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. -
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Age and Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Keras implementation of a CNN network for age and gender estimation. This is a Keras implementation of a CNN for estimating age and gender from a face image [1, 2]. In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained... -
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StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. ... -
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GluonNLP
NLP made easy
GluonNLP is a toolkit that helps you solve NLP problems. It provides easy-to-use tools that helps you load the text data, process the text data, and train models. 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... -
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NSFW Detection Machine Learning Model
Keras model of NSFW detector
Keras model of NSFW detector, NSFW Detection Machine Learning Model. -
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AlphaPy
Python AutoML for Trading Systems and Sports Betting
...Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow. Develop trading systems and analyze portfolios using MarketFlow and Quantopian's pyfolio. -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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Multilingual Speech Synthesis
An implementation of Tacotron 2 that supports multilingual experiments
This repository provides synthesized samples, training and evaluation data, source code, and parameters for the paper One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech. It contains an implementation of Tacotron 2 that supports multilingual experiments and that implements different approaches to encoder parameter sharing. It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice cloning, End-to-End Code-Switched TTS with Mix of Monolingual Recordings, and Contextual Parameter Generation for Universal Neural Machine Translation. ... -
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Frontend Regression Validator (FRED)
Visual regression tool used to compare baseline and updated instances
...The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. It has an internal queue and can process websites in parallel depending on the amount of RAM and CPUs (or GPUs) available.
