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Title: GitHub - h2oai/awesome-h2o: A curated list of research, applications and projects built using the H2O Machine Learning platform

Open Graph Title: GitHub - h2oai/awesome-h2o: A curated list of research, applications and projects built using the H2O Machine Learning platform

X Title: GitHub - h2oai/awesome-h2o: A curated list of research, applications and projects built using the H2O Machine Learning platform

Description: A curated list of research, applications and projects built using the H2O Machine Learning platform - h2oai/awesome-h2o

Open Graph Description: A curated list of research, applications and projects built using the H2O Machine Learning platform - h2oai/awesome-h2o

X Description: A curated list of research, applications and projects built using the H2O Machine Learning platform - h2oai/awesome-h2o

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community@h2o.ai

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https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#blog-posts--tutorials
Using H2O AutoML to simplify training process (and also predict wine quality)https://enjoymachinelearning.com/posts/h2o-auto-machine-learning/
Visualizing ML Models with LIMEhttps://uc-r.github.io/lime
Parallel Grid Search in H2O https://www.pavel.cool/h2o-3/h2o-parallel-grid-search/
Importing, Inspecting and Scoring with MOJO models inside H2Ohttps://www.pavel.cool/h2o-3/h2o-mojo-import/
Artificial Intelligence Made Easy with H2O.ai: A Comprehensive Guide to Modeling with H2O.ai and AutoML in Pythonhttps://towardsdatascience.com/artificial-intelligence-made-easy-187ecb90c299
Anomaly Detection With Isolation Forests Using H2Ohttps://dzone.com/articles/anomaly-detection-with-isolation-forests-using-h2o-1
Predicting residential property prices in Bratislava using recipes - H2O Machine learninghttps://www.michal-kapusta.com/post/2018-11-02-predicting-residential-property-prices-in-bratislava-using-recipes-h2o-machine-learning-part-ii/
Inspecting Decision Trees in H2Ohttps://dzone.com/articles/inspecting-decision-trees-in-h2o
Gentle Introduction to AutoML from H2O.aihttps://medium.com/analytics-vidhya/gentle-introduction-to-automl-from-h2o-ai-a42b393b4ba2
Machine Learning With H2O — Hands-On Guide for Data Scientistshttps://dzone.com/articles/machine-learning-with-h2o-hands-on-guide-for-data
Using machine learning with LIME to understand employee churnhttp://www.business-science.io/business/2018/06/25/lime-local-feature-interpretation.html
Analytics at Scale: h2o, Apache Spark and R on AWS EMRhttps://redoakstrategic.com/h2oaws/
Automated and unmysterious machine learning in cancer detectionhttps://kkulma.github.io/2017-11-07-automated_machine_learning_in_cancer_detection/
Time series machine learning with h2o+timetkhttp://www.business-science.io/code-tools/2017/10/28/demo_week_h2o.html
Sales Analytics: How to use machine learning to predict and optimize product backordershttp://www.business-science.io/business/2017/10/16/sales_backorder_prediction.html
HR Analytics: Using machine learning to predict employee turnoverhttp://www.business-science.io/business/2017/09/18/hr_employee_attrition.html
Autoencoders and anomaly detection with machine learning in fraud analytics https://shiring.github.io/machine_learning/2017/05/01/fraud
Building deep neural nets with h2o and rsparkling that predict arrhythmia of the hearthttps://shiring.github.io/machine_learning/2017/02/27/h2o
Predicting food preferences with sparklyr (machine learning)https://shiring.github.io/machine_learning/2017/02/19/food_spark
Moving largish data from R to H2O - spam detection with Enron emailshttps://ellisp.github.io/blog/2017/02/18/svmlite
Deep learning & parameter tuning with mxnet, h2o package in Rhttp://blog.hackerearth.com/understanding-deep-learning-parameter-tuning-with-mxnet-h2o-package-in-r
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#books
Big data in psychiatry and neurology, Chapter 11: A scalable medication intake monitoring systemhttps://www.elsevier.com/books/big-data-in-psychiatry-and-neurology/moustafa/978-0-12-822884-5
Hands on Time Series with Rhttps://www2.packtpub.com/big-data-and-business-intelligence/hands-time-series-analysis-r
Mastering Machine Learning with Spark 2.xhttps://www.packtpub.com/product/mastering-machine-learning-with-spark-2-x/9781785283451
Machine Learning Using Rhttps://www.amazon.com/Machine-Learning-Using-Karthik-Ramasubramanian/dp/1484223330
Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AIhttps://www.amazon.com/Practical-Machine-Learning-H2O-Techniques/dp/149196460X
Disruptive Analyticshttp://link.springer.com/book/10.1007/978-1-4842-1311-7
Computer Age Statistical Inference: Algorithms, Evidence, and Data Sciencehttps://web.stanford.edu/~hastie/CASI/
R Deep Learning Essentialshttps://www.packtpub.com/big-data-and-business-intelligence/r-deep-learning-essentials
Spark in Actionhttps://www.manning.com/books/spark-in-action
Handbook of Big Datahttps://www.crcpress.com/Handbook-of-Big-Data/Buhlmann-Drineas-Kane-van-der-Laan/p/book/9781482249071
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#research-papers
Automated machine learning: AI-driven decision making in business analyticshttps://www.sciencedirect.com/science/article/pii/S2667305323000133
Water-Quality Prediction Based on H2O AutoML and Explainable AI Techniqueshttps://www.mdpi.com/2073-4441/15/3/475
Which model to choose? Performance comparison of statistical and machine learning models in predicting PM2.5 from high-resolution satellite aerosol optical depthhttps://www.sciencedirect.com/science/article/abs/pii/S1352231022002291?dgcid=coauthor
Prospective validation of a transcriptomic severity classifier among patients with suspected acute infection and sepsis in the emergency departmenthttps://pubmed.ncbi.nlm.nih.gov/35467566/
Depression Level Prediction in People with Parkinson’s Disease during the COVID-19 Pandemichttps://embc.embs.org/2021/
Machine Learning-based Meal Detection Using Continuous Glucose Monitoring on Healthy Participants: An Objective Measure of Participant Compliance to Protocolhttps://embc.embs.org/2021/
Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youthhttps://onlinelibrary.wiley.com/doi/full/10.1002/hbm.25565
Appendectomy during the COVID-19 pandemic in Italy: a multicenter ambispective cohort study by the Italian Society of Endoscopic Surgery and new technologies (the CRAC study)https://pubmed.ncbi.nlm.nih.gov/34219197/
Forecasting Canadian GDP Growth with Machine Learninghttps://carleton.ca/economics/wp-content/uploads/cewp21-05.pdf
Morphological traits of reef corals predict extinction risk but not conservation statushttps://onlinelibrary.wiley.com/doi/10.1111/geb.13321
Machine Learning as a Tool for Improved Housing Price Predictionhttps://openaccess.nhh.no/nhh-xmlui/bitstream/handle/11250/2739783/masterthesis.pdf?sequence=1
Citizen Science Data Show Temperature-Driven Declines in Riverine Sentinel Invertebrateshttps://pubs.acs.org/doi/10.1021/acs.estlett.0c00206
Predicting Risk of Delays in Postal Deliveries with Neural Networks and Gradient Boosting Machineshttps://www.diva-portal.org/smash/get/diva2:1467609/FULLTEXT01.pdf
Stock Market Analysis using Stacked Ensemble Learning Methodhttps://github.com/malhartakle/MastersDissertation/blob/master/Research%20Project%20Report.pdf
H2O AutoML: Scalable Automatic Machine Learninghttps://www.automl.org/wp-content/uploads/2020/07/AutoML_2020_paper_61.pdf
Single-cell mass cytometry on peripheral blood identifies immune cell subsets associated with primary biliary cholangitishttps://www.nature.com/articles/s41598-020-69358-4
Prediction of the functional impact of missense variants in BRCA1 and BRCA2 with BRCA-MLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190647/
Innovative deep learning artificial intelligence applications for predicting relationships between individual tree height and diameter at breast heighthttps://doi.org/10.1186/s40663-020-00226-3
An Open Source AutoML Benchmarkhttps://www.automl.org/wp-content/uploads/2019/06/automlws2019_Paper45.pdf
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligencehttps://arxiv.org/abs/2002.04803
Human actions recognition in video scenes from multiple camera viewpointshttps://www.sciencedirect.com/science/article/pii/S1389041718308970
Extending MLP ANN hyper-parameters Optimization by using Genetic Algorithmhttps://ieeexplore.ieee.org/document/8489520/authors#authors
askMUSIC: Leveraging a Clinical Registry to Develop a New Machine Learning Model to Inform Patients of Prostate Cancer Treatments Chosen by Similar Menhttps://doi.org/10.1016/j.eururo.2018.09.050
Machine Learning Methods to Perform Pricing Optimization. A Comparison with Standard GLMshttp://www.variancejournal.org/articlespress/articles/Machine-Spedicato.pdf
Comparative Performance Analysis of Neural Networks Architectures on H2O Platform for Various Activation Functionshttps://arxiv.org/abs/1707.04940
Algorithmic trading using deep neural networks on high frequency datahttps://link.springer.com/chapter/10.1007/978-3-319-66963-2_14
Generic online animal activity recognition on collar tagshttps://dl.acm.org/citation.cfm?id=3124407
Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learninghttps://link.springer.com/content/pdf/10.1007%2Fs10705-017-9870-x.pdf
Robust and flexible estimation of data-dependent stochastic mediation effects: a proposed method and example in a randomized trial settinghttps://arxiv.org/pdf/1707.09021.pdf
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competitionhttps://arxiv.org/abs/1707.02641
Using deep learning to predict the mortality of leukemia patientshttps://qspace.library.queensu.ca/bitstream/handle/1974/15929/Muthalaly_Reena%20S_201707_MSC.pdf
Use of a machine learning framework to predict substance use disorder treatment successhttp://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0175383&type=printable
Ultra-wideband antenna-induced error prediction using deep learning on channel response datahttps://www.kn.e-technik.tu-dortmund.de/.cni-bibliography/publications/cni-publications/Tiemann2017a.pdf
Inferring passenger types from commuter eigentravel matriceshttp://www.tandfonline.com/doi/abs/10.1080/21680566.2017.1291377?journalCode=ttrb20
Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500http://www.sciencedirect.com/science/article/pii/S0377221716308657
Identifying IT purchases anomalies in the Brazilian government procurement system using deep learninghttp://ieeexplore.ieee.org/document/7838233/?reload=true
Predicting recovery of credit operations on a Brazilian bankhttp://ieeexplore.ieee.org/abstract/document/7838243/
Deep learning anomaly detection as support fraud investigation in Brazilian exports and anti-money launderinghttp://ieeexplore.ieee.org/abstract/document/7838276/
Deep learning and association rule mining for predicting drug response in cancerhttps://doi.org/10.1101/070490
The value of points of interest information in predicting cost-effective charging infrastructure locationshttp://www.rsm.nl/fileadmin/Images_NEW/ECFEB/The_value_of_points_of_interest_information.pdf
Adaptive modelling of spatial diversification of soil classification units. Journal of Water and Land Developmenthttps://www.degruyter.com/downloadpdf/j/jwld.2016.30.issue-1/jwld-2016-0029/jwld-2016-0029.xml
Scalable ensemble learning and computationally efficient variance estimationhttp://www.stat.berkeley.edu/~ledell/papers/ledell-phd-thesis.pdf
Superchords: decoding EEG signals in the millisecond rangehttps://doi.org/10.7287/peerj.preprints.1265v1
Understanding random forests: from theory to practicehttps://github.com/glouppe/phd-thesis
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#benchmarks
Are categorical variables getting lost in your random forests?http://roamanalytics.com/2016/10/28/are-categorical-variables-getting-lost-in-your-random-forests/
Deep learning in Rhttp://www.rblog.uni-freiburg.de/2017/02/07/deep-learning-in-r/
Szilard's machine learning benchmarkhttps://github.com/szilard/benchm-ml
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#presentations
Pipelines for model deploymenthttps://www.slideshare.net/rocalabern/digital-origin-pipelines-for-model-deployment
Machine learning with H2O.aihttps://speakerdeck.com/szilard/machine-learning-with-h2o-dot-ai-la-h2o-meetup-at-at-and-t-jan-2017
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#courses
University of San Francisco (USF) Distributed Data System Class (MSDS 697)https://github.com/dianewoodbridge/2020-msds697-example
University of Oslo: Introduction to Automatic and Scalable Machine Learning with H2O and Rhttps://www.ub.uio.no/english/courses-events/events/all-libraries/2019/research-bazaar-2019.html
UCLA: Tools in Data Science (STATS 418)https://github.com/szilard/teach-data-science-UCLA-master-appl-stats
GWU: Data Mining (Decision Sciences 6279)https://github.com/jphall663/GWU_data_mining
University of Cape Town: Analytics Modulehttp://www.stats.uct.ac.za/stats/study/postgrad/honours
Coursera: How to Win a Data Science Competition: Learn from Top Kagglershttps://www.coursera.org/learn/competitive-data-science
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#software
modeltime.h2o R packagehttps://business-science.github.io/modeltime.h2o/
Evaporatehttps://github.com/ML4LHS/Evaporate
herehttps://twitter.com/kdpsinghlab/status/1367992786239242248
splash R packagehttps://github.com/ML4LHS/splash
herehttps://twitter.com/kdpsinghlab/status/1367809740705792008
h2oparsnip R packagehttps://github.com/stevenpawley/h2oparsnip
parsniphttps://parsnip.tidymodels.org/
Spin up PySpark and PySparkling on AWShttps://github.com/kcrandall/EMR_Spark_Automation
Forecast the US demand for electricityhttps://github.com/RamiKrispin/USelectricity
dashboardhttps://ramikrispin.github.io/USelectricity/
h2o3-pamhttps://github.com/navdeep-G/h2o3-pam
h2o3-gapstathttps://github.com/navdeep-G/h2o3-gapstat
https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#license
https://creativecommons.org/publicdomain/zero/1.0/
H2O.aihttp://h2o.ai
github.com/h2oai/h2o-3https://github.com/h2oai/h2o-3
data-science https://patch-diff.githubusercontent.com/topics/data-science
machine-learning https://patch-diff.githubusercontent.com/topics/machine-learning
awesome https://patch-diff.githubusercontent.com/topics/awesome
deep-learning https://patch-diff.githubusercontent.com/topics/deep-learning
h2o https://patch-diff.githubusercontent.com/topics/h2o
awesome-list https://patch-diff.githubusercontent.com/topics/awesome-list
h2oai https://patch-diff.githubusercontent.com/topics/h2oai
Readme https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#readme-ov-file
Code of conduct https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#coc-ov-file
Contributing https://patch-diff.githubusercontent.com/h2oai/awesome-h2o#contributing-ov-file
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Activityhttps://patch-diff.githubusercontent.com/h2oai/awesome-h2o/activity
Custom propertieshttps://patch-diff.githubusercontent.com/h2oai/awesome-h2o/custom-properties
392 starshttps://patch-diff.githubusercontent.com/h2oai/awesome-h2o/stargazers
142 watchinghttps://patch-diff.githubusercontent.com/h2oai/awesome-h2o/watchers
75 forkshttps://patch-diff.githubusercontent.com/h2oai/awesome-h2o/forks
Report repository https://patch-diff.githubusercontent.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Fh2oai%2Fawesome-h2o&report=h2oai+%28user%29
Releaseshttps://patch-diff.githubusercontent.com/h2oai/awesome-h2o/releases
Packages 0https://patch-diff.githubusercontent.com/orgs/h2oai/packages?repo_name=awesome-h2o
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https://github.com
Termshttps://docs.github.com/site-policy/github-terms/github-terms-of-service
Privacyhttps://docs.github.com/site-policy/privacy-policies/github-privacy-statement
Securityhttps://github.com/security
Statushttps://www.githubstatus.com/
Communityhttps://github.community/
Docshttps://docs.github.com/
Contacthttps://support.github.com?tags=dotcom-footer

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