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fathom - A framework for extracting meaning from web pages
Find meaning in the web.
semantic-extraction scoring ranking clusteringprotoactor-go - Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
Introducing cross platform actor support between Go and C#.Can I use this? The Go implementation is still in beta, there are users using Proto Actor for Go in production already. But be aware that the API might change over time until 1.0.
grpc actor-model actors cross-platform protobuf akka clustering distributed-computingLeaflet.markercluster - Marker Clustering plugin for Leaflet
Provides Beautiful Animated Marker Clustering functionality for Leaflet, a JS library for interactive maps. See the included examples for usage.
leaflet map mapping clustering leaflet-plugins gis cluster leaflet-plugin mapsTensorFlow-Book - Accompanying source code for Machine Learning with TensorFlow
This is the official code repository for Machine Learning with TensorFlow. Get started with machine learning using TensorFlow, Google's latest and greatest machine learning library.
tensorflow machine-learning regression convolutional-neural-networks logistic-regression book reinforcement-learning autoencoder linear-regression classification clusteringazk - azk is a lightweight open source development environment orchestration tool
azk lets developers easily and quickly install and configure their development environments. Period. For further details, please see the docs.
cli sysadmin process-manager docker clustering devops dev-ops azuki orchestrate orquestrationOryx 2 - Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning
The Oryx open source project provides infrastructure for lambda-architecture applications on top of Spark, Spark Streaming and Kafka. On this, it provides further support for real-time, large scale machine learning, and end-to-end applications of this support for common machine learning use cases, like recommendations, clustering, classification and regression.
lambda lambda-architecture oryx apache-spark machine-learning kafka classification clusteringDAT8 - General Assembly's 2015 Data Science course in Washington, DC
Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15).
data-science machine-learning scikit-learn data-analysis pandas jupyter-notebook course linear-regression logistic-regression model-evaluation naive-bayes natural-language-processing decision-trees ensemble-learning clustering regular-expressions web-scraping data-visualization data-cleaningmlr - mlr: Machine Learning in R
Please cite our JMLR paper [bibtex]. Some parts of the package were created as part of other publications. If you use these parts, please cite the relevant work appropriately. An overview of all mlr related publications can be found here.
machine-learning data-science tuning cran r-package predictive-modeling classification regression statistics r survival-analysis imbalance-correction tutorial mlr learners hyperparameters-optimization feature-selection multilabel-classification clustering stackingCluster - Easy Map Annotation Clustering 📍
Cluster is an easy map annotation clustering library. This repository uses an efficient method (QuadTree) to aggregate pins into a cluster. The Annotation class exposes a style property that allows you to customize the appearance.
map cluster clustering mapkit ios annotations apple cocoapods carthagepractical-machine-learning-with-python - Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system
"Data is the new oil" is a saying which you must have heard by now along with the huge interest building up around Big Data and Machine Learning in the recent past along with Artificial Intelligence and Deep Learning. Besides this, data scientists have been termed as having "The sexiest job in the 21st Century" which makes it all the more worthwhile to build up some valuable expertise in these areas. Getting started with machine learning in the real world can be overwhelming with the vast amount of resources out there on the web. "Practical Machine Learning with Python" follows a structured and comprehensive three-tiered approach packed with concepts, methodologies, hands-on examples, and code. This book is packed with over 500 pages of useful information which helps its readers master the essential skills needed to recognize and solve complex problems with Machine Learning and Deep Learning by following a data-driven mindset. By using real-world case studies that leverage the popular Python Machine Learning ecosystem, this book is your perfect companion for learning the art and science of Machine Learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute Machine Learning systems and projects successfully.
machine-learning deep-learning text-analytics classification clustering natural-language-processing computer-vision data-science spacy nltk scikit-learn prophet time-series-analysis convolutional-neural-networks tensorflow keras statsmodels pandas deep-neural-networkstext-analytics-with-python - Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer
Derive useful insights from your data using Python. Learn the techniques related to natural language processing and text analytics, and gain the skills to know which technique is best suited to solve a particular problem. A structured and comprehensive approach is followed in this book so that readers with little or no experience do not find themselves overwhelmed. You will start with the basics of natural language and Python and move on to advanced analytical and machine learning concepts. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems.
text-analytics text-summarization text-classification natural-language natural-language-processing clustering sentiment semantic sentiment-analysis nltk stanford-nlp spacy pattern scikit-learn gensimFaiss - A library for efficient similarity search and clustering of dense vectors.
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research.
clustering similarity-search artificial-intelligence gpuMLJ.jl - A Julia machine learning framework
New to MLJ? Start here. Wanting to integrate an existing machine learning model into the MLJ framework? Start here.
data-science machine-learning statistics pipeline clustering julia pipelines regression tuning classification ensemble-learning predictive-modeling tuning-parameters stackingdepth_clustering - :taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor
This is a fast and robust algorithm to segment point clouds taken with Velodyne sensor into objects. It works with all available Velodyne sensors, i.e. 16, 32 and 64 beam ones. I recommend using a virtual environment in your catkin workspace (<catkin_ws> in this readme) and will assume that you have it set up throughout this readme. Please update your commands accordingly if needed. I will be using pipenv that you can install with pip.
fast real-time clustering point-cloud range ros lidar depth segmentation pcl catkin velodyne-sensor velodyne depth-image range-image depth-clusteringprotoactor-dotnet - Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
Ultra-fast, distributed, cross-platform actors.This is the .NET repository for Proto Actor.
actors clustering proto-actor akka distributed-systems distributed-computingsupercluster - A crazy fast geospatial point clustering library for browsers and Node.
A very fast JavaScript library for geospatial point clustering for browsers and Node.Loads an array of GeoJSON Feature objects. Each feature's geometry must be a GeoJSON Point. Once loaded, index is immutable.
clustering algorithm computational-geometry maps geospatial markersawesome-single-cell - List of software packages for single-cell data analysis, including RNA-seq, ATAC-seq, etc
List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Contributions welcome... Gender bias at conferences is a well known problem (http://www.sciencemag.org/careers/2015/07/countering-gender-bias-conferences). Creating a list of potential speakers can help mitigate this bias and a community of people developing and maintaining helps to further diversify this list beyond smaller networks.
rna-seq-data gene-expression scrna-seq-data bioinformatics awesome-list dimensionality-reduction cell-cycle atac-seq analysis cell-differentiation clusteringmoosefs - MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System
MooseFS is a Petabyte Open Source Network Distributed File System. It is easy to deploy and maintain, fault tolerant, highly performing, easily scalable, POSIX compliant. MooseFS Linux Client uses FUSE. MooseFS macOS Client uses FUSE for macOS.
dfs software-defined-storage posix filesystem file-system distributed-file-system clustering distributed-storage distributed-computing fuse big-data snapshot storage-tiering high-availability scalability storage moosefs hadoop posix-compliantPythonMachineLearning - Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
numpy statistics pandas matplotlib regression scikit-learn classification principal-component-analysis clustering decision-trees random-forest dimensionality-reduction neural-network deep-learning artificial-intelligence data-science machine-learning k-nearest-neighbours naive-bayessuperpoint_graph - Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning https://arxiv.org/pdf/1904.02113. To switch to the stable branch with only SPG, switch to release.
semantic clustering point-cloud pytorch lidar segmentation partition semantic-segmentation large-scale ply-files superpoint-graphs
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