TedsdsApache Spark - Turbofan Engine Degradation Simulation Data Set example in Apache Spark
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DeepbayesBayesian methods in deep learning Summer School
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ArchiveArchive of presentations
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Python Web ScrapingWhen performing data science tasks, it's common to want to use data found on the internet. You'll usually be able to access this data in csv format, or via an Application Programming Interface (API). However, there are times when the data you want can only be accessed as part of a web page. In cases like this, you'll want to use a technique called web scraping to get the data from the web page into a format you can work with in your analysis.
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Core StoriesAll the notebooks for the analysis of Emotional Arcs within the Project Gutenberg corpus, see "The emotional arcs of stories are dominated by six basic shapes"
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Altair CatplotUtility to generate plots with categorical variables using Altair.
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QuaiQuAI is QNAP’s AI Developer Package, for data scientists and developers, to quickly build, train, optimize and deploy machine learning models, on top of QNAP NAS.
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NotebooksAn attempt to formalize my thoughts. A pythonic approach to mental housekeeping
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SageHome of the Semi-Analytic Galaxy Evolution (SAGE) galaxy formation model
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Ismir2016Instructions for reproducing the research described in the paper "Tempo Estimation for Music Loops and a Simple Confidence Measure"
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Azure Webapp W CntkDeployment template for Azure WebApp, CNTK, Python 3 (x64) and sample model
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AcademiaiaarCompilado de cursos y material de capacitación en herramientas de IA y DataScience.
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Crime AnalysisAssociation Rule Mining from Spatial Data for Crime Analysis
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Icon2017Repository for the ICON 2017 hackathon 'multivoxel pattern analysis (MVPA) of fMRI data in Python'
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Grab AiforseaEntry for Grab's AI for S.E.A. challenge
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How Long Can You RunRepository containing a dataSet and a python notebook to perform data analysis about workouts. The data was gathered from Health Graph API - Runkeeper
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Seq 2 Seq OcrHandwritten text recognition with Keras
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TutorialsA project for developing tutorials for Streams
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Ds OptimusHow to do data science with Optimus, Spark and Python.
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MotivesextractorExtract Polyphonic Musical Motives from Audio Recordings
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Seq2seq Attention ModelAn implementation for attention model in Keras for sequence to sequence model.
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FrolsidentificationA set of Matlab/Octave files that performs a method of Nonlinear System Identification.
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Machine Learning Starter KitThe fastest way for developers and managers to gain practical ML knowledge and to apply it to their own projects.
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Strata dataA repo of sample data for our PyData Tutorial!
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Nlp tutorialsOverview of NLP tools and techniques in python
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Brain Tumor Segmentation KerasKeras implementation of the multi-channel cascaded architecture introduced in the paper "Brain Tumor Segmentation with Deep Neural Networks"
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KaggleMy kaggle competition solution and notebook
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MppcaMixtures of Probabilistic Principal Component Analysers implementation in python
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Dsx TutorialsA collection of tutorials, demos, and use cases for IBM Data Science Experience http://datascience.ibm.com/
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Mj583J583 Advanced Interactive Media
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CryptotechnicalsPresentation and code from Cryptocurrency Technical Trading strategy meeting. Dec 7th 2017
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Intrusion Detection SystemI have tried some of the machine learning and deep learning algorithm for IDS 2017 dataset. The link for the dataset is here: http://www.unb.ca/cic/datasets/ids-2017.html. By keeping Monday as the training set and rest of the csv files as testing set, I tried one class SVM and deep CNN model to check how it works. Here the Monday dataset contains only normal data and rest of the days contains both normal and attacked data. Also, from the same university (UNB) for the Tor and Non Tor dataset, I tried K-means clustering and Stacked LSTM models in order to check the classification of multiple labels.
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TsaTime Series Anomaly Detection Toolkit
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Attend Infer Repeat PytorchS.M.Ali Eslam et.al. Attend, Infer, Repeat: Fast Scene Understanding with Generative Models ICML16
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Crunchbase MlMerge and Acquisitions Prediction based on M&A information from Crunchbase.
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Spark NotebooksCollection of useful notebooks to be used with the Spark Notebook (https://github.com/andypetrella/spark-notebook)
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Tensorflow2 Generative ModelsImplementations of a number of generative models in Tensorflow 2. GAN, VAE, Seq2Seq, VAEGAN, GAIA, Spectrogram Inversion. Everything is self contained in a jupyter notebook for easy export to colab.
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