Machine Learning tool
http://www.semanlink.net/tag/machine_learning_tool
Documents tagged with Machine Learning toolspaCy sur Twitter : "NEW transformer library for PyTorch: curated-transformers!"
http://www.semanlink.net/doc/2023/07/spacy_sur_twitter_new_transf
> - Supports state-of-the-art models, including LLMs like Falcon & LLaMA
> - 4-bit & 8-bit inference
> - Built from composable, reusable components
2023-07-14T02:11:49ZMPS backend — PyTorch master documentation
http://www.semanlink.net/doc/2023/05/mps_backend_pytorch_master_do
2023-05-14T13:12:55Zexplosion/prodigy-openai-recipes: ✨ Bootstrap annotation with zero- & few-shot learning via OpenAI GPT-3
http://www.semanlink.net/doc/2023/02/explosion_prodigy_openai_recipe
> example code on how to combine zero- and few-shot learning with a small annotation effort
2023-02-11T10:45:36ZMatthew Honnibal sur Twitter : "We've been working on new prodi.gy workflows that let you use the @OpenAI API to kickstart your annotations, via zero- or few-shot learning. ..."
http://www.semanlink.net/doc/2022/12/matthew_honnibal_sur_twitter_
2022-12-20T00:03:04ZHorace He @ neurips sur Twitter : "Eager mode was what made PyTorch successful. So why did we feel the need to depart from eager mode in PyTorch 2.0?..."
http://www.semanlink.net/doc/2022/12/horace_he_neurips_sur_twitter
> Answer: it's the damn hardware!
2022-12-10T12:23:51ZSantiago sur Twitter : "If you have an Apple M1 or M2 and don't take advantage of its GPU, I'm about to change your life..."
http://www.semanlink.net/doc/2022/10/santiago_sur_twitter_if_you_
> These instructions allow TensorFlow to use your GPU
2022-10-07T19:33:41ZGoogle AI Blog: TensorStore for High-Performance, Scalable Array Storage
http://www.semanlink.net/doc/2022/09/google_ai_blog_tensorstore_for
Use Case: 3D Brain Mapping
2022-09-23T02:24:43ZModeling DNA Sequences with PyTorch | by Erin Wilson | Sep, 2022 | Towards Data Science
http://www.semanlink.net/doc/2022/09/modeling_dna_sequences_with_pyt
2022-09-18T09:44:07ZActive Learning with AutoNLP and Prodigy
http://www.semanlink.net/doc/2022/09/active_learning_with_autonlp_an
2022-09-06T18:07:58ZA framework for designing document processing solutions
http://www.semanlink.net/doc/2022/09/a_framework_for_designing_docum
2022-09-02T10:25:44ZKarl Higley sur Twitter : "Many ANN search tools (e.g. FAISS, ScaNN) allow you to provide multiple points as part of the same query..."
http://www.semanlink.net/doc/2022/08/karl_higley_sur_twitter_many
> Puzzled why more retrieval models don’t take advantage of this. Give me 100 neighbors of ten points, not 1000 neighbors of one point! (Then score and order them.)
2022-08-20T18:11:10ZHow to Build a Semantic Search Engine With Transformers and Faiss | by Kostas Stathoulopoulos | Towards Data Science
http://www.semanlink.net/doc/2022/01/how_to_build_a_semantic_search_
2022-01-29T17:33:32ZJames Briggs sur Twitter : *free* course on vector similarity search and Faiss..."
http://www.semanlink.net/doc/2021/10/james_briggs_sur_twitter_fre
2021-10-16T13:39:33Zscikit-learn Pipelines meet Knowledge Graphs - The Python kgextension Package ESWC 2021
http://www.semanlink.net/doc/2021/06/scikit_learn_pipelines_meet_kno
> The kgextension package allows to access and use Linked Open Data to augment existing datasets for improving a classification/clustering task.
How to create data analysis pipeline using background knowledge from knowledge graphs
[Github](https://github.com/om-hb/kgextension/blob/master/examples/book_genre_prediction.ipynb)
2021-06-10T15:59:47ZTeddy Koker sur Twitter : "Torchsort, an implementation of "Fast Differentiable Sorting and Ranking" in PyTorch"
http://www.semanlink.net/doc/2021/03/teddy_koker_sur_twitter_torc
2021-03-25T17:24:25Zarogozhnikov/einops: Deep learning operations reinvented (for pytorch, tensorflow, jax and others)
http://www.semanlink.net/doc/2021/02/arogozhnikov_einops_deep_learn
2021-02-03T15:37:19Zscikit-multilearn: Multi-Label Classification in Python
http://www.semanlink.net/doc/2020/09/scikit_multilearn_multi_label_
2020-09-16T18:21:54Zscikit-multilearn/scikit-multilearn: A scikit-learn based module for multi-label et. al. classification
http://www.semanlink.net/doc/2020/08/scikit_multilearn_scikit_multil
2020-08-12T12:47:05ZFinding similar documents with transformers · Codegram
http://www.semanlink.net/doc/2020/07/finding_similar_documents_with_
2020-07-10T09:30:37Zawslabs/dgl-ke: package for learning large-scale knowledge graph embeddings.
http://www.semanlink.net/doc/2020/07/awslabs_dgl_ke_package_for_lea
2020-07-07T19:15:54Zfacebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.
http://www.semanlink.net/doc/2020/06/facebookresearch_faiss_a_libra
Algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. Faiss is written in C++ with complete wrappers for Python/numpy.
[paper](https://arxiv.org/abs/1702.08734)
2020-06-09T20:51:47ZSiamese Network for Image and Text similarity using Keras
http://www.semanlink.net/doc/2020/01/siamese_network_keras_for_image
2020-01-22T16:50:08ZGitHub - OpenNMT/OpenNMT-py: Open Source Neural Machine Translation in PyTorch
http://www.semanlink.net/doc/2020/01/github_opennmt_opennmt_py_op
2020-01-17T12:57:35ZBuilding a Search Engine with BERT and TensorFlow - Towards Data Science
http://www.semanlink.net/doc/2020/01/building_a_search_engine_with_b
[somewhat related](/doc/2020/01/elasticsearch_meets_bert_build)
2020-01-12T17:13:45ZHow to build deep neural network for custom NER with Keras
http://www.semanlink.net/doc/2020/01/how_to_build_deep_neural_networ
2020-01-07T11:57:40ZNamed Entity Recognition with Pytorch Transformers – Pierre-Yves Vandenbussche
http://www.semanlink.net/doc/2019/12/named_entity_recognition_with_p
> How to have a SotA identification of Disease and Chemical entities in 10 lines of code!
2019-12-11T16:29:53ZOne Shot learning, Siamese networks and Triplet Loss with Keras
http://www.semanlink.net/doc/2019/10/one_shot_learning_siamese_netw
2019-10-13T19:00:46ZThe dangers of reshaping and other fun mistakes I’ve learnt from PyTorch
http://www.semanlink.net/doc/2019/09/the_dangers_of_reshaping_and_ot
2019-09-14T11:29:48ZIntroducing Neural Structured Learning in TensorFlow
http://www.semanlink.net/doc/2019/09/introducing_neural_structured_l
Neural Structured Learning (NSL) is an open source framework for training deep neural networks with structured signals. It implements Neural Graph Learning, which enables developers to train neural networks using graphs.
2019-09-03T19:01:32ZAn easy introduction to Pytorch for Neural Networks
http://www.semanlink.net/doc/2019/08/an_easy_introduction_to_pytorch
2019-08-09T10:25:24Zhuggingface/pytorch-transformers: A library of state-of-the-art pretrained models for NLP
http://www.semanlink.net/doc/2019/07/huggingface_pytorch_transformer
(formerly known as pytorch-pretrained-bert)
2019-07-27T10:20:52ZWhy and How we use Pangeo at CNES - pangeo - Medium
http://www.semanlink.net/doc/2019/07/why_and_how_we_use_pangeo_at_cn
2019-07-17T11:21:15ZPipelines and composite estimators / ColumnTransformer for heterogeneous data — scikit-learn documentation
http://www.semanlink.net/doc/2019/07/pipelines_and_composite_estimat
[blog post with sample code](https://towardsdatascience.com/columntransformer-meets-natural-language-processing-da1f116dd69f)
2019-07-02T01:01:11ZOne Shot Learning with Siamese Networks using Keras
http://www.semanlink.net/doc/2019/06/one_shot_learning_with_siamese_
the network is learning a **similarity function**, which takes two images as input and expresses how similar they are.
> Assume that we want to build face recognition system for a small organization with only 10 employees...
2019-06-28T19:00:27ZTowards Reproducible Research with PyTorch Hub | PyTorch
http://www.semanlink.net/doc/2019/06/towards_reproducible_research_w
2019-06-11T11:39:01ZPyTorch-BigGraph: Faster embeddings of large graphs - Facebook Code
https://code.fb.com/open-source/pytorch-biggraph/
> A new tool from Facebook AI Research that enables training of multi-relation graph embeddings for very large graphs. PyTorch-BigGraph (PBG) handles graphs with billions of nodes and trillions of edges. Since PBG is written in PyTorch, researchers and engineers can easily swap in their own loss functions, models, and other components.
[Github](https://github.com/facebookresearch/PyTorch-BigGraph), [Blog post](https://ai.facebook.com/blog/open-sourcing-pytorch-biggraph-for-faster-embeddings-of-extremely-large-graphs)
2019-05-12T12:23:13ZRadek Osmulski sur Twitter : "You would expect a difference in row access times depending on the type of a sparse matrix, but I didn't realize the difference would be so big!
https://twitter.com/radekosmulski/status/1124766298469277696
2019-05-05T10:32:30ZIntroduction to PyTorch Code Examples
https://cs230-stanford.github.io/pytorch-getting-started.html
2019-04-03T13:57:45Zhuggingface/pytorch-pretrained-BERT: The Big-&-Extending-Repository-of-Transformers: Pretrained PyTorch models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.
https://github.com/huggingface/pytorch-pretrained-BERT
2019-03-15T22:38:21ZFrançois Chollet sur Twitter : a crash course on everything you need to know to use TensorFlow 2.0 + Keras
https://twitter.com/fchollet/status/1105139360226140160
2019-03-12T22:48:43ZTraining Cutting-Edge Neural Networks with Tensor2Tensor and 10 lines of code
https://medium.com/data-from-the-trenches/training-cutting-edge-neural-networks-with-tensor2tensor-and-10-lines-of-code-10973c030b8
2019-01-21T10:58:18ZWhat is torch.nn really? — PyTorch Tutorials 1.0.0
https://pytorch.org/tutorials/beginner/nn_tutorial.html
2019-01-16T22:21:35ZCombining numerical and text features in (deep) neural networks - Digital Thinking
http://digital-thinking.de/deep-learning-combining-numerical-and-text-features-in-deep-neural-networks/
2018-12-12T11:38:27ZHow to Use the Keras Functional API for Deep Learning
https://machinelearningmastery.com/keras-functional-api-deep-learning/
2018-12-12T11:35:54ZDeepLearning Images Revision M13/14. PyTorch 1.0. Git Integration. Smaller Boot Time.
https://blog.kovalevskyi.com/deeplearning-images-revision-m13-14-pytorch-1-0-git-integration-smaller-boot-time-1cb5bda59968
2018-12-12T08:29:37ZProdigy · An annotation tool for AI, Machine Learning & NLP
https://prodi.gy/
> a machine teaching tool
2018-12-09T09:52:31ZAdvances in few-shot learning: reproducing results in PyTorch
https://towardsdatascience.com/advances-in-few-shot-learning-reproducing-results-in-pytorch-aba70dee541d
2018-12-02T10:21:44Ziliaschalkidis/ELMo-keras: Re-implementation of ELMo on Keras
https://github.com/iliaschalkidis/ELMo-keras
based on the tensorflow implementation presented by Allen NLP
2018-11-14T21:32:37ZIntroduction to Amazon SageMaker Object2Vec | AWS Machine Learning Blog
https://aws.amazon.com/fr/blogs/machine-learning/introduction-to-amazon-sagemaker-object2vec/
ex of uses:
- Collaborative recommendation system
- Multi-label document classification
- Sentence embeddings
2018-11-10T11:53:00ZHow to boost a Keras based neural network using AdaBoost? - Stack Overflow
https://stackoverflow.com/questions/39063676/how-to-boost-a-keras-based-neural-network-using-adaboost
2018-10-28T01:00:34ZTensorFlow: how to load and save models at every epoch so you never lose time or data.
https://twitter.com/TensorFlow/status/1055538593941409792
2018-10-26T16:31:02ZPractical Text Classification With Python and Keras – Real Python
https://realpython.com/python-keras-text-classification/
2018-10-25T08:39:17ZTensorFlow.js
https://js.tensorflow.org/
2018-10-10T11:27:13ZDeploy Your First Deep Learning Model On Kubernetes With Python, Keras, Flask, and Docker
https://medium.com/analytics-vidhya/deploy-your-first-deep-learning-model-on-kubernetes-with-python-keras-flask-and-docker-575dc07d9e76
2018-10-07T12:50:42ZTraining on TPU
https://colab.research.google.com/github/tensorflow/tpu/blob/master/tools/colab/fashion_mnist.ipynb
2018-10-05T08:19:26Zdatas-frame – Tabular Data in Scikit-Learn and Dask-ML
https://tomaugspurger.github.io/sklearn-dask-tabular.html
2018-09-17T18:06:59ZNamed Entity Recognition and Classification with Scikit-Learn
https://towardsdatascience.com/named-entity-recognition-and-classification-with-scikit-learn-f05372f07ba2
2018-09-16T10:15:39ZStrategies to scale computationally: bigger data — scikit-learn documentation
http://scikit-learn.org/stable/modules/scaling_strategies.html
using out-of-core learning
2018-09-15T18:42:54ZFor what tasks is Pytorch preferable to Tensorflow? - Quora
https://www.quora.com/For-what-tasks-is-Pytorch-preferable-to-Tensorflow
2018-08-28T09:23:39ZWhat is Candidate Sampling
https://www.tensorflow.org/extras/candidate_sampling.pdf
2018-07-07T15:04:54ZAurélien Geron sur Twitter : "In @TensorFlow 1.9, it is much easier to use Keras with the Data API..."
https://twitter.com/aureliengeron/status/1005483669929299969
"In @TensorFlow 1.9, it is much easier to use Keras with the Data API: just pass data iterators, specify the number of steps per epoch, and you're good to go! Plus it works in both graph mode and eager mode, kudos to the TF team!… https://t.co/EH3hY50N0o"
2018-06-10T09:18:12ZHow to do Unsupervised Clustering with Keras – Chengwei Zhang – Medium
https://medium.com/@chengweizhang2012/how-to-do-unsupervised-clustering-with-keras-9e1284448437
2018-06-09T09:23:35ZCloud TPU – Accélérateurs de ML pour TensorFlow | Google Cloud
https://cloud.google.com/tpu/
2018-05-31T16:23:57ZModule google/universal-sentence-encoder | TensorFlow
https://www.tensorflow.org/hub/modules/google/universal-sentence-encoder-large/1
[Paper presented at EMNLP 2018](https://aclanthology.coli.uni-saarland.de/papers/D18-2029/d18-2029)
2018-05-23T16:35:31ZTesting Tensorflow code
https://guillaumegenthial.github.io/testing.html
2018-05-21T12:04:22ZHow to use Dataset in TensorFlow – Towards Data Science
https://towardsdatascience.com/how-to-use-dataset-in-tensorflow-c758ef9e4428
2018-04-21T11:41:38ZText Classification with TensorFlow Estimators
http://ruder.io/text-classification-tensorflow-estimators/
2018-04-17T14:19:22ZPart-of-Speech tagging tutorial with the Keras Deep Learning library - Cdiscount TechBlog
https://techblog.cdiscount.com/part-speech-tagging-tutorial-keras-deep-learning-library/
2018-04-13T10:18:20ZMulticlass and multilabel algorithms — scikit-learn documentation
http://scikit-learn.org/stable/modules/multiclass.html
2018-03-17T14:38:19ZIntro to text classification with Keras: automatically tagging Stack Overflow posts | Google Cloud Big Data and Machine Learning Blog
https://cloud.google.com/blog/big-data/2017/10/intro-to-text-classification-with-keras-automatically-tagging-stack-overflow-posts
2018-03-04T16:59:49ZCodes of Interest: Using Bottleneck Features for Multi-Class Classification in Keras and TensorFlow
http://www.codesofinterest.com/2017/08/bottleneck-features-multi-class-classification-keras.html
2018-03-04T16:49:06ZGitHub - tensorflow/models: Models and examples built with TensorFlow
https://github.com/tensorflow/models
2018-02-28T23:55:28ZA Benchmark of Text Classification in PyTorch
https://github.com/wabyking/TextClassificationBenchmark
2018-02-28T23:52:55ZTopic Modeling with Scikit Learn – Aneesha Bakharia – Medium
https://medium.com/@aneesha/topic-modeling-with-scikit-learn-e80d33668730
2017-12-05T09:54:22ZImplementing a CNN for Text Classification in TensorFlow – WildML
http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
2017-11-06T18:56:50ZMultivariate Time Series Forecasting with LSTMs in Keras - Machine Learning Mastery
https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/
2017-10-25T15:58:38ZLSTM with word2vec embeddings | Kaggle
https://www.kaggle.com/lystdo/lstm-with-word2vec-embeddings
2017-10-25T15:50:14ZHow to Use Word Embedding Layers for Deep Learning with Keras - Machine Learning Mastery
https://machinelearningmastery.com/use-word-embedding-layers-deep-learning-keras/
Keras Embedding Layer requires that the input data be integer encoded, so that each word is represented by a unique integer. This data preparation step can be performed using the Tokenizer API also provided with Keras.
The Embedding layer is initialized with random weights and will learn an embedding for all of the words in the training dataset.
- Example of Learning an Embedding
- Example of Using Pre-Trained GloVe Embedding
2017-10-25T15:40:03ZKeras examples directory
https://github.com/fchollet/keras/tree/master/examples
2017-10-25T14:41:57ZUsing Gensim Word2Vec Embeddings in Keras | Ben Bolte's Blog
http://ben.bolte.cc/blog/2016/gensim.html
2017-10-23T09:05:11ZRecurrent neural networks and LSTM tutorial in Python and TensorFlow - Adventures in Machine Learning
http://adventuresinmachinelearning.com/recurrent-neural-networks-lstm-tutorial-tensorflow/
2017-10-23T08:53:16ZA Word2Vec Keras tutorial
http://adventuresinmachinelearning.com/word2vec-keras-tutorial/
2017-10-23T01:22:35ZUsing pre-trained word embeddings in a Keras model
https://blog.keras.io/using-pre-trained-word-embeddings-in-a-keras-model.html
Text classification using pre-trained GloVe embeddings (loaded into a frozen Keras Embedding layer) and a [convolutional neural network](/tag/convolutional_neural_network)
2017-10-23T01:07:38ZInstalling TensorFlow on Mac OS X | TensorFlow
https://www.tensorflow.org/install/install_mac
2017-10-23T00:19:06ZTensorflow sucks
http://nicodjimenez.github.io/2017/10/08/tensorflow.html
see [What do people think of the TensorFlow sucks article? on Quora](https://www.quora.com/What-do-people-think-of-the-TensorFlow-sucks-article)
2017-10-16T14:34:28ZA ten-minute introduction to sequence-to-sequence learning in Keras
https://blog.keras.io/a-ten-minute-introduction-to-sequence-to-sequence-learning-in-keras.html
Sequence-to-sequence learning (Seq2Seq) is about training models to convert sequences from one domain (e.g. sentences in English) to sequences in another domain (e.g. the same sentences translated to French).
2017-09-30T10:54:53ZTensorFlow Neural Machine Translation (seq2seq) Tutorial
https://github.com/tensorflow/nmt
2017-09-18T14:14:51ZHow does Keras compare to other Deep Learning frameworks like Tensor Flow, Theano, or Torch? - Quora
https://www.quora.com/How-does-Keras-compare-to-other-Deep-Learning-frameworks-like-Tensor-Flow-Theano-or-Torch
2017-09-09T13:49:22ZVector Representations of Words | TensorFlow
https://www.tensorflow.org/tutorials/word2vec
2017-08-28T15:41:07Zscikit-learn documentation: General examples
http://scikit-learn.org/stable/auto_examples/index.html#
2017-06-20T10:11:03Z10 Top Open Source Artificial Intelligence Tools for Linux
http://www.tecmint.com/open-source-artificial-intelligence-tools-softwares-linux/
2017-01-04T14:32:37ZUnderstanding neural networks with TensorFlow Playground | Google Cloud Big Data and Machine Learning Blog | Google Cloud Platform
https://cloud.google.com/blog/big-data/2016/07/understanding-neural-networks-with-tensorflow-playground
2016-07-27T10:05:31ZHow to Get Started with Java Machine Learning | Takipi Blog
http://blog.takipi.com/how-to-get-started-with-java-machine-learning/
2016-07-08T11:45:56ZMini AI app using TensorFlow and Shiny – Opiate for the masses
http://opiateforthemass.es/articles/mini-ai-app-using-tensorflow-and-shiny/
2016-01-15T01:15:01ZSoftware links « Deep Learning
http://deeplearning.net/software_links/
2016-01-12T18:36:13Z10 Free Deep Learning Tools - Butler Analytics
http://www.butleranalytics.com/10-free-deep-learning-tools/
2016-01-12T18:35:11ZSample pipeline for text feature extraction and evaluation — scikit-learn documentation
http://scikit-learn.org/stable/auto_examples/model_selection/grid_search_text_feature_extraction.html#example-model-selection-grid-search-text-feature-extraction-py
2016-01-12T00:45:15ZCross-validation: evaluating estimator performance — scikit-learn documentation
http://scikit-learn.org/stable/modules/cross_validation.html
2016-01-11T17:52:23ZSupport Vector Machines — scikit-learn documentation
http://scikit-learn.org/stable/modules/svm.html
2016-01-11T17:20:26ZTensorFlow is Terrific – A Sober Take on Deep Learning Acceleration
http://www.kdnuggets.com/2015/12/tensor-flow-terrific-deep-learning-library.html
2016-01-07T00:43:58ZHow To Learn Any Machine Learning Tool - Machine Learning Mastery
http://machinelearningmastery.com/how-to-learn-any-machine-learning-tool/
2015-12-30T00:27:54ZJava Machine Learning
http://machinelearningmastery.com/java-machine-learning/
2015-12-30T00:25:58ZSimple end-to-end TensorFlow examples | Bcomposes
https://bcomposes.wordpress.com/2015/11/26/simple-end-to-end-tensorflow:-examples/?utm_content=buffer46554&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
2015-12-21T19:05:46ZResearch Blog: TensorFlow - Google’s latest machine learning system, open sourced for everyone
http://googleresearch.blogspot.fr/2015/11/tensorflow-googles-latest-machine_9.html?m=1
2015-11-09T18:52:15ZTensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
http://download.tensorflow.org/paper/whitepaper2015.pdf
2015-11-09T18:49:56ZAutograd for Torch
https://blog.twitter.com/2015/autograd-for-torch
new framework for simplifying deep learning research: autograd for Torch
2015-11-07T10:48:06ZThe Glowing Python: Combining Scikit-Learn and NTLK
http://glowingpython.blogspot.fr/2013/07/combining-scikit-learn-and-ntlk.html
2015-10-21T18:43:13ZWorking With Text Data — scikit-learn documentation
http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
scikit-learn tutorial about analysing a collection of labelled text documents :
- load the file contents and the categories
- extract feature vectors (count, tf, tf-idf)
- train a linear model to perform categorization
- use a grid search strategy (to find a good configuration of both the feature extraction components and the classifier)
2015-10-21T10:08:08Zscikit learn: machine learning map
http://scikit-learn.org/stable/_static/ml_map.png
2015-10-19T10:51:16Zscikit-learn: machine learning in Python
http://scikit-learn.org
2015-10-16T00:17:32ZIntroducing DataFrames in Spark for Large Scale Data Science | Databricks
https://databricks.com/blog/2015/02/17/introducing-dataframes-in-spark-for-large-scale-data-science.html
2015-02-19T01:18:27ZApache Spark
https://spark.apache.org/
"a fast and general engine for large-scale data processing" "fast and general-purpose cluster computing system"<br/>
Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.
2014-12-18T11:43:50ZGreat list of resources - NoSQL, Big Data, Machine Learning and more | GitHub - Data Science Central
http://www.datasciencecentral.com/profiles/blogs/great-list-of-resources-nosql-big-data-ml-and-much-more-posted-on?overrideMobileRedirect=1
2014-07-23T19:35:28ZSapping Attention: When you have a MALLET, everything looks like a nail
http://sappingattention.blogspot.fr/2012/11/when-you-have-mallet-everything-looks.html
2014-04-25T12:44:00Ztopic-modeling-tool - A graphical user interface tool for topic modeling - Google Project Hosting
http://code.google.com/p/topic-modeling-tool/
2014-04-23T10:56:23ZReal-Time Topic Modeling of Microblogs
http://www.oracle.com/technetwork/articles/java/micro-1925135.html
2014-04-22T18:21:08Zpallet - A professionalization of the UMass project "Mallet" - Google Project Hosting
http://code.google.com/p/pallet/
2014-04-22T17:39:23ZAlgorithms - Apache Mahout - Apache Software Foundation
https://cwiki.apache.org/confluence/display/MAHOUT/Algorithms
2013-09-09T15:23:04ZGetting Started with Topic Modeling and MALLET
http://programminghistorian.org/lessons/topic-modeling-and-mallet
- what topic modeling is and why you might want to employ it<br/>
- how to install and work with the MALLET natural language processing toolkit to do so
2012-09-20T10:47:05ZMALLET homepage
http://mallet.cs.umass.edu/
2012-09-20T10:41:45Z