Search Results for "machine learning python" - Page 5
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Showing 135 open source projects for "machine learning python"
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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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Spectral Python
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more. -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. -
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TensorWatch
Debugging, monitoring and visualization for Python Machine Learning
TensorWatch is an open source debugging and visualization platform created by Microsoft Research to support machine learning, deep learning, and reinforcement learning workflows. It enables developers to observe training behavior in real time through interactive visualizations, primarily within Jupyter Notebook environments. The tool treats most data interactions as streams, allowing flexible routing, storage, and visualization of metrics generated during model training. ... -
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Deep Learning with PyTorch
Latest techniques in deep learning and representation learning
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. -
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Inviwo
Interactive Visualization Workshop
...Built in C++ with a modular, extensible architecture, Inviwo combines a visual editor (for creating data pipelines) with a powerful runtime engine that supports real-time rendering, interaction, and GPU-accelerated processing. It’s widely used in scientific domains for building and sharing visualizations of complex data such as medical imaging, simulations, and machine learning models. The platform supports both novice users through its graphical interface and advanced users through scripting and plugin development. -
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Facets
Visualizations for machine learning datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. -
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OpenFace
A state-of-the-art facial behavior analysis toolkit
OpenFace is an advanced facial behavior analysis toolkit intended for computer vision and machine learning researchers, those in the affective computing community, and those who are simply interested in creating interactive applications based on facial behavior analysis. The OpenFace toolkit is capable of performing several complex facial analysis tasks, including facial landmark detection, eye-gaze estimation, head pose estimation and facial action unit recognition. -
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TensorFlow.jl
A Julia wrapper for TensorFlow
A wrapper around TensorFlow, a popular open-source machine learning framework from Google. -
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CrimeKgAssitant
Crime assistant including crime type prediction
CrimeKgAssitant is a Chinese-language legal NLP project that combines offense prediction, consultation classification, automated answers, and knowledge graph queries. It organizes data around criminal charges, sentencing cases, legal question-and-answer pairs, and related legal information. A multiclass model predicts likely offense categories from written case descriptions using document embeddings and a support vector machine. Separate classifiers sort consultation questions into... -
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GMOL
A tool for 3D genome structure visualization
...This software was built upon the pre-existing Jmol package by Prof. Cheng's group. The software is developed in Prof. Jianlin Cheng's Bioinformatics, Data Mining and Machine Learning Laboratory in the Computer Science Department at the University of Missouri - Columbia, USA. The project is supported by the National Science Foundation (grant no. DBI1149224). If you use GMOL in your research, please cite: Nowotny, Jackson, Avery Wells, Oluwatosin Oluwadare, Lingfei Xu, Renzhi Cao, Tuan Trieu, Chenfeng He, and Jianlin Cheng. ... -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. -
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AI learning
AiLearning, data analysis plus machine learning practice
We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,... -
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Merlin.jl
Deep Learning for Julia
Merlin is a deep learning framework written in Julia. It aims to provide a fast, flexible and compact deep learning library for machine learning. Merlin is tested against Julia 1.0 on Linux, OS X, and Windows (x64). -
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Seldon Server
Machine learning platform and recommendation engine on Kubernetes
...Seldon Core is a progression of the goals of the Seldon-Server project but also a more restricted focus to solving the final step in a machine learning project which is serving models in production. Seldon Server is a machine learning platform that helps your data science team deploy models into production. It provides an open-source data science stack that runs within a Kubernetes Cluster. You can use Seldon to deploy machine learning and deep learning models into production on-premise or in the cloud (e.g. ... -
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DeepLearningProject
An in-depth machine learning tutorial
This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. -
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Neuro
The Neuro crypto currency
The Neuro NRO cryptocurrency is designed to support solutions of machine learning tasks, big data and neural networks. Neuro is a scientific-technical project uniting scientists, engineers and programmers inspired by the idea to build something big, kind and bright. From the first stages of work, we will be engaged in the development of new architectures and algorithms of neural networks. Someday we will undoubtedly enter the annual ImageNet Challenge contest to compete with such giants as GoogLeNet Inception and Microsoft ResNet. ... -
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Rodeo
A data science IDE for Python
...Rodeo makes it very easy for its users to explore what is created by them and also alongside allows the users to Inspect, interact, compare data frames, plots and even much more. It is an IDE that has been built especially for data science/Machine Learning in Python and you can also very simply think of it as a light weight alternative to the IPython Notebook. -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data... -
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Data Science Specialization
Course materials for the Data Science Specialization on Coursera
...The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow. -
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Open Cezeri Library
Effective Linear Algebra and Computer Vision Library with JAVA
...To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. Studies on accesing Leapmotion and Kinect is still under-development. 2- Machine learning: It uses Weka Software tool and some personel coded ML algorithms 3- CMatrix: Special matrix library called as CMatrix meaning Cezeri Maztrix Class. ... -
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ankus
Data Mining and Machine Learning Algorithms based on MapReduce
[The feature of ankus] * ankus is a 'web-based big data mining project and tool'. - MapReduce-based data mining/machine learning algorithms library - Hadoop-based distributed bigdata system - offering a web-based GUI for easy use [The ankus project & License] * The ankus project consists of three as an open source. * ankus has Dual licensed under the community and commercial licenses. * community license is following GPLv3 - Some algorithms in Core Project do not under the OSS License [Demonstration Site] http://www.openankus.org:18080 [Official website & E-mail] www.openankus.org ankus@openankus.org [ankus video list] http://bit.ly/ankus_video [community] http://www.facebook.com/groups/openankus (Korean Groups) http://www.facebook.com/openankus (English Groups) http://bit.ly/ankus_forum (Google groups user forum) -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures,...
