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| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#step-2-build-simple-supervised-models |
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| https://www.dropbox.com/s/krvhmt7z8zxhl7f/ISLRv2_website.pdf?dl=0 | https://www.dropbox.com/s/krvhmt7z8zxhl7f/ISLRv2_website.pdf?dl=0 |
| https://github.com/aiskunks/Skunks_Skool/tree/main/I2SL_Statistical_Learning |
| https://github.com/aiskunks/Skunks_Skool/tree/main/I2SL_Statistical_Learning | https://github.com/aiskunks/Skunks_Skool/tree/main/I2SL_Statistical_Learning |
| https://www.youtube.com/playlist?list=PL5-da3qGB5IDvuFPNoSqheihPOQNJpzyy | https://www.youtube.com/playlist?list=PL5-da3qGB5IDvuFPNoSqheihPOQNJpzyy |
| https://www.youtube.com/playlist?list=PL5-da3qGB5IBSSCPANhTgrw82ws7w_or9 | https://www.youtube.com/playlist?list=PL5-da3qGB5IBSSCPANhTgrw82ws7w_or9 |
| https://youtube.com/playlist?list=PL5-da3qGB5IC4vaDba5ClatUmFppXLAh | https://youtube.com/playlist?list=PL5-da3qGB5IC4vaDba5ClatUmFppXLAh |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#step-3 |
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| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#algorithms |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#supervised-learning |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#unsupervised-learning |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#semi-supervised-learning |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#reinforcement-learning |
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| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#intensive-programs |
| S2DS | https://www.s2ds.org/ |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#moocs |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| Coursera Introduction to Data Science | https://www.coursera.org/specializations/data-science |
| CS 171 Visualization | https://www.cs171.org/#!index.md |
| Process Mining: Data science in Action | https://www.coursera.org/learn/process-mining |
| Oxford Deep Learning | https://www.cs.ox.ac.uk/projects/DeepLearn/ |
| Oxford Deep Learning - video | https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu |
| Oxford Machine Learning | https://www.cs.ox.ac.uk/research/ai_ml/index.html |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#tutorials |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| 1000 Data Science Projects | https://cloud.blobcity.com/#/ps/explore |
| #tidytuesday | https://github.com/rfordatascience/tidytuesday |
| Data science your way | https://github.com/jadianes/data-science-your-way |
| PySpark Cheatsheet | https://github.com/kevinschaich/pyspark-cheatsheet |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#free-courses |
| Data Scientist with R | https://www.datacamp.com/tracks/data-scientist-with-r |
| Data Scientist with Python | https://www.datacamp.com/tracks/data-scientist-with-python |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#toolboxes---environment |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| The Data Science Lifecycle Process | https://github.com/dslp/dslp |
| Data Science Lifecycle Template Repo | https://github.com/dslp/dslp-repo-template |
| RexMex | https://github.com/AstraZeneca/rexmex |
| ChemicalX | https://github.com/AstraZeneca/chemicalx |
| PyTorch Geometric Temporal | https://github.com/benedekrozemberczki/pytorch_geometric_temporal |
| Little Ball of Fur | https://github.com/benedekrozemberczki/littleballoffur |
| Karate Club | https://github.com/benedekrozemberczki/karateclub |
| ML Workspace | https://github.com/ml-tooling/ml-workspace |
| Neptune.ai | https://neptune.ai |
| steppy | https://github.com/minerva-ml/steppy |
| steppy-toolkit | https://github.com/minerva-ml/steppy-toolkit |
| Datalab from Google | https://cloud.google.com/datalab/docs/ |
| Hortonworks Sandbox | https://www.cloudera.com/downloads/hortonworks-sandbox.html |
| R | https://www.r-project.org/ |
| RStudio | https://www.rstudio.com |
| Python - Pandas - Anaconda | https://www.anaconda.com |
| Pandas GUI | https://github.com/adrotog/PandasGUI |
| Scikit-Learn | https://scikit-learn.org/stable/ |
| NumPy | https://numpy.org/ |
| Vaex | https://vaex.io/ |
| SciPy | https://scipy.org/ |
| Data Science Toolbox | https://www.coursera.org/learn/data-scientists-tools |
| Data Science Toolbox | https://datasciencetoolbox.org/ |
| Wolfram Data Science Platform | https://www.wolfram.com/data-science-platform/ |
| Datadog | https://www.datadoghq.com/ |
| Variance | https://variancecharts.com/ |
| Kite Development Kit | https://kitesdk.org/docs/current/index.html |
| Domino Data Labs | https://www.dominodatalab.com |
| Apache Flink | https://flink.apache.org/ |
| Apache Hama | https://hama.apache.org/ |
| Weka | https://www.cs.waikato.ac.nz/ml/weka/ |
| Octave | https://www.gnu.org/software/octave/ |
| Apache Spark | https://spark.apache.org/ |
| Hydrosphere Mist | https://github.com/Hydrospheredata/mist |
| Data Mechanics | https://www.datamechanics.co |
| Caffe | https://caffe.berkeleyvision.org/ |
| Torch | https://torch.ch/ |
| Nervana's python based Deep Learning Framework | https://github.com/NervanaSystems/neon |
| Skale | https://github.com/skale-me/skale |
| Aerosolve | https://airbnb.io/aerosolve/ |
| Intel framework | https://github.com/intel/idlf |
| Datawrapper | https://www.datawrapper.de/ |
| github.com | https://github.com/datawrapper/datawrapper |
| Tensor Flow | https://www.tensorflow.org/ |
| Natural Language Toolkit | https://www.nltk.org/ |
| nlp-toolkit for node.js | https://www.npmjs.com/package/nlp-toolkit |
| Julia | https://julialang.org |
| IJulia | https://github.com/JuliaLang/IJulia.jl |
| Apache Zeppelin | https://zeppelin.apache.org/ |
| Featuretools | https://github.com/alteryx/featuretools |
| Optimus | https://github.com/hi-primus/optimus |
| Albumentations | https://github.com/albumentations-team/albumentations |
| DVC | https://github.com/iterative/dvc |
| Lambdo | https://github.com/asavinov/lambdo |
| Feast | https://github.com/feast-dev/feast |
| Polyaxon | https://github.com/polyaxon/polyaxon |
| LightTag | https://www.lighttag.io/ |
| UBIAI | https://ubiai.tools |
| Trains | https://github.com/allegroai/clearml |
| Hopsworks | https://github.com/logicalclocks/hopsworks |
| MindsDB | https://github.com/mindsdb/mindsdb |
| Lightwood | https://github.com/mindsdb/lightwood |
| AWS Data Wrangler | https://github.com/awslabs/aws-data-wrangler |
| Amazon Rekognition | https://aws.amazon.com/rekognition/ |
| Amazon Textract | https://aws.amazon.com/textract/ |
| Amazon Lookout for Vision | https://aws.amazon.com/lookout-for-vision/ |
| Amazon CodeGuru | https://aws.amazon.com/codeguru/ |
| CML | https://github.com/iterative/cml |
| Dask | https://dask.org/ |
| Statsmodels | https://www.statsmodels.org/stable/index.html |
| Gensim | https://radimrehurek.com/gensim/ |
| spaCy | https://spacy.io/ |
| Grid Studio | https://github.com/ricklamers/gridstudio |
| Python Data Science Handbook | https://github.com/jakevdp/PythonDataScienceHandbook |
| Shapley | https://github.com/benedekrozemberczki/shapley |
| DAGsHub | https://dagshub.com |
| Deepnote | https://deepnote.com |
| Valohai | https://valohai.com |
| PyMC3 | https://docs.pymc.io/ |
| PyStan | https://pypi.org/project/pystan/ |
| hmmlearn | https://pypi.org/project/hmmlearn/ |
| Chaos Genius | https://github.com/chaos-genius/chaos_genius/ |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#machine-learning-libraries |
| scikit-learn | https://scikit-learn.org/ |
| scikit-multilearn | https://github.com/scikit-multilearn/scikit-multilearn |
| sklearn-expertsys | https://github.com/tmadl/sklearn-expertsys |
| scikit-feature | https://github.com/jundongl/scikit-feature |
| scikit-rebate | https://github.com/EpistasisLab/scikit-rebate |
| seqlearn | https://github.com/larsmans/seqlearn |
| sklearn-bayes | https://github.com/AmazaspShumik/sklearn-bayes |
| sklearn-crfsuite | https://github.com/TeamHG-Memex/sklearn-crfsuite |
| sklearn-deap | https://github.com/rsteca/sklearn-deap |
| sigopt_sklearn | https://github.com/sigopt/sigopt-sklearn |
| sklearn-evaluation | https://github.com/edublancas/sklearn-evaluation |
| scikit-image | https://github.com/scikit-image/scikit-image |
| scikit-opt | https://github.com/guofei9987/scikit-opt |
| scikit-posthocs | https://github.com/maximtrp/scikit-posthocs |
| pystruct | https://github.com/pystruct/pystruct |
| Shogun | https://www.shogun-toolbox.org/ |
| xLearn | https://github.com/aksnzhy/xlearn |
| cuML | https://github.com/rapidsai/cuml |
| causalml | https://github.com/uber/causalml |
| mlpack | https://github.com/mlpack/mlpack |
| MLxtend | https://github.com/rasbt/mlxtend |
| modAL | https://github.com/modAL-python/modAL |
| Sparkit-learn | https://github.com/lensacom/sparkit-learn |
| hyperlearn | https://github.com/danielhanchen/hyperlearn |
| dlib | https://github.com/davisking/dlib |
| RuleFit | https://github.com/christophM/rulefit |
| pyGAM | https://github.com/dswah/pyGAM |
| Deepchecks | https://github.com/deepchecks/deepchecks |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#deep-learning |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#pytorch |
| PyTorch | https://github.com/pytorch/pytorch |
| torchvision | https://github.com/pytorch/vision |
| torchtext | https://github.com/pytorch/text |
| torchaudio | https://github.com/pytorch/audio |
| ignite | https://github.com/pytorch/ignite |
| PyTorchNet | https://github.com/pytorch/tnt |
| PyToune | https://github.com/GRAAL-Research/poutyne |
| skorch | https://github.com/skorch-dev/skorch |
| PyVarInf | https://github.com/ctallec/pyvarinf |
| pytorch_geometric | https://github.com/pyg-team/pytorch_geometric |
| GPyTorch | https://github.com/cornellius-gp/gpytorch |
| pyro | https://github.com/pyro-ppl/pyro |
| Catalyst | https://github.com/catalyst-team/catalyst |
| pytorch_tabular | https://github.com/manujosephv/pytorch_tabular |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#tensorflow |
| TensorFlow | https://github.com/tensorflow/tensorflow |
| TensorLayer | https://github.com/tensorlayer/TensorLayer |
| TFLearn | https://github.com/tflearn/tflearn |
| Sonnet | https://github.com/deepmind/sonnet |
| tensorpack | https://github.com/tensorpack/tensorpack |
| TRFL | https://github.com/deepmind/trfl |
| Polyaxon | https://github.com/polyaxon/polyaxon |
| NeuPy | https://github.com/itdxer/neupy |
| tfdeploy | https://github.com/riga/tfdeploy |
| tensorflow-upstream | https://github.com/ROCmSoftwarePlatform/tensorflow-upstream |
| TensorFlow Fold | https://github.com/tensorflow/fold |
| tensorlm | https://github.com/batzner/tensorlm |
| TensorLight | https://github.com/bsautermeister/tensorlight |
| Mesh TensorFlow | https://github.com/tensorflow/mesh |
| Ludwig | https://github.com/ludwig-ai/ludwig |
| TF-Agents | https://github.com/tensorflow/agents |
| TensorForce | https://github.com/tensorforce/tensorforce |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#keras |
| Keras | https://keras.io |
| keras-contrib | https://github.com/keras-team/keras-contrib |
| Hyperas | https://github.com/maxpumperla/hyperas |
| Elephas | https://github.com/maxpumperla/elephas |
| Hera | https://github.com/keplr-io/hera |
| Spektral | https://github.com/danielegrattarola/spektral |
| qkeras | https://github.com/google/qkeras |
| keras-rl | https://github.com/keras-rl/keras-rl |
| Talos | https://github.com/autonomio/talos |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#visualization-tools---environments |
| altair | https://altair-viz.github.io/ |
| addepar | https://opensource.addepar.com/ember-charts/#/overview |
| amcharts | https://www.amcharts.com/ |
| anychart | https://www.anychart.com/ |
| bokeh | https://bokeh.org/ |
| slemma | https://slemma.com/ |
| cartodb | https://cartodb.github.io/odyssey.js/ |
| Cube | https://square.github.io/cube/ |
| d3plus | https://d3plus.org/ |
| Data-Driven Documents(D3js) | https://d3js.org/ |
| datahero | https://datahero.com/ |
| dygraphs | https://dygraphs.com/ |
| ECharts | https://echarts.baidu.com/index-en.html |
| exhibit | https://www.simile-widgets.org/exhibit/ |
| gephi | https://gephi.org/ |
| ggplot2 | https://ggplot2.tidyverse.org/ |
| Glue | http://docs.glueviz.org/en/latest/index.html |
| Google Chart Gallery | https://developers.google.com/chart/interactive/docs/gallery |
| highcarts | https://www.highcharts.com/ |
| import.io | https://www.import.io/ |
| ipychart | https://nicohlr.gitlab.io/ipychart/ |
| jqplot | https://www.jqplot.com/ |
| Matplotlib | https://matplotlib.org/ |
| nvd3 | https://nvd3.org/ |
| Netron | https://github.com/lutzroeder/netron |
| Opendata-tools | https://opendata-tools.org/en/visualization/ |
| Openrefine | https://openrefine.org/ |
| plot.ly | https://plot.ly/ |
| raw | https://rawgraphs.io |
| Seaborn | https://seaborn.pydata.org/ |
| techanjs | https://techanjs.org/ |
| Timeline | https://timeline.knightlab.com/ |
| variancecharts | https://variancecharts.com/index.html |
| vida | https://vida.io/ |
| vizzu | https://github.com/vizzuhq/vizzu-lib |
| Wrangler | https://vis.stanford.edu/wrangler/ |
| r2d3 | https://www.r2d3.us/visual-intro-to-machine-learning-part-1/ |
| NetworkX | https://networkx.org/ |
| Redash | https://redash.io/ |
| C3 | https://c3js.org/ |
| TensorWatch | https://github.com/microsoft/tensorwatch |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#journals-publications-and-magazines |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| ICML | https://icml.cc/2015/ |
| GECCO | https://gecco-2019.sigevo.org/index.html/HomePage |
| epjdatascience | https://epjdatascience.springeropen.com/ |
| Journal of Data Science | https://jds-online.org/journal/JDS |
| Big Data Research | https://www.journals.elsevier.com/big-data-research |
| Journal of Big Data | https://journalofbigdata.springeropen.com/ |
| Big Data & Society | https://journals.sagepub.com/home/bds |
| Data Science Journal | https://www.jstage.jst.go.jp/browse/dsj |
| datatau.com/news | https://www.datatau.com/news |
| Data Science Trello Board | https://trello.com/b/rbpEfMld/data-science |
| Medium Data Science Topic | https://medium.com/tag/data-science |
| Towards Data Science Genetic Algorithm Topic | https://towardsdatascience.com/introduction-to-genetic-algorithms-including-example-code-e396e98d8bf3#:~:text=A%20genetic%20algorithm%20is%20a,offspring%20of%20the%20next%20generation. |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#presentations |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| Building Data Start-Ups: Fast, Big, and Focused | https://www.slideshare.net/medriscoll/driscoll-strata-buildingdatastartups25may2011clean |
| How to win data science competitions with Deep Learning | https://www.slideshare.net/0xdata/how-to-win-data-science-competitions-with-deep-learning |
| Full-Stack Data Scientist | https://www.slideshare.net/AlexeyGrigorev/fullstack-data-scientist |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#podcasts |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| AI at Home | https://podcasts.apple.com/us/podcast/data-science-at-home/id1069871378 |
| AI Today | https://www.cognilytica.com/aitoday/ |
| Adversarial Learning | https://adversariallearning.com/ |
| Becoming a Data Scientist | https://www.becomingadatascientist.com/category/podcast/ |
| Chai time Data Science | https://www.youtube.com/playlist?list=PLLvvXm0q8zUbiNdoIazGzlENMXvZ9bd3x |
| Data Crunch | https://datacrunchcorp.com/data-crunch-podcast/ |
| Data Engineering Podcast | https://www.dataengineeringpodcast.com/ |
| Data Science at Home | https://datascienceathome.com/ |
| Data Science Mixer | https://community.alteryx.com/t5/Data-Science-Mixer/bg-p/mixer |
| Data Skeptic | https://dataskeptic.com/ |
| Data Stories | https://datastori.es/ |
| Datacast | https://jameskle.com/writes/category/Datacast |
| DataFramed | https://www.datacamp.com/community/podcast |
| DataTalks.Club | https://anchor.fm/datatalksclub |
| Gradient Dissent | https://wandb.ai/fully-connected/gradient-dissent |
| Learning Machines 101 | https://www.learningmachines101.com/ |
| Let's Data (Brazil) | https://www.youtube.com/playlist?list=PLn_z5E4dh_Lj5eogejMxfOiNX3nOhmhmM |
| Linear Digressions | https://lineardigressions.com/ |
| Not So Standard Deviations | https://nssdeviations.com/ |
| O'Reilly Data Show Podcast | https://www.oreilly.com/radar/topics/oreilly-data-show-podcast/ |
| Partially Derivative | https://partiallyderivative.com/ |
| Superdatascience | https://www.superdatascience.com/podcast/ |
| The Data Engineering Show | https://www.dataengineeringshow.com/ |
| The Radical AI Podcast | https://www.radicalai.org/ |
| The Robot Brains Podcast | https://www.therobotbrains.ai/ |
| What's The Point | https://fivethirtyeight.com/tag/whats-the-point/ |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#books |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| Exploring Data Science | https://www.manning.com/books/exploring-data-science |
| Exploring the Data Jungle | https://www.manning.com/books/exploring-the-data-jungle |
| Classic Computer Science Problems in Python | https://www.manning.com/books/classic-computer-science-problems-in-python |
| Math for Programmers | https://www.manning.com/books/math-for-programmers |
| R in Action, Third Edition | https://www.manning.com/books/r-in-action-third-edition |
| Data Science Bookcamp | https://www.manning.com/books/data-science-bookcamp |
| Data Science Thinking: The Next Scientific, Technological and Economic Revolution | https://www.springer.com/gp/book/9783319950914 |
| Applied Data Science: Lessons Learned for the Data-Driven Business | https://www.springer.com/gp/book/9783030118204 |
| The Data Science Handbook | https://www.amazon.com/Data-Science-Handbook-Field-Cady/dp/1119092949 |
| Essential Natural Language Processing | https://www.manning.com/books/getting-started-with-natural-language-processing |
| Mining Massive Datasets | https://www.mmds.org/ |
| Pandas in Action | https://www.manning.com/books/pandas-in-action |
| Genetic Algorithms and Genetic Programming | https://www.taylorfrancis.com/books/9780429141973 |
| Genetic algorithms in search, optimization, and machine learning | https://www2.fiit.stuba.sk/~kvasnicka/Free%20books/Goldberg_Genetic_Algorithms_in_Search.pdf |
| Advances in Evolutionary Algorithms | https://www.intechopen.com/books/advances_in_evolutionary_algorithms |
| Genetic Programming: New Approaches and Successful Applications | https://www.intechopen.com/books/genetic-programming-new-approaches-and-successful-applications |
| Evolutionary Algorithms | https://www.intechopen.com/books/evolutionary-algorithms |
| Advances in Genetic Programming, Vol. 3 | https://www.cs.bham.ac.uk/~wbl/aigp3/ |
| Global Optimization Algorithms: Theory and Application | https://www.it-weise.de/projects/book.pdf |
| Genetic Algorithms and Evolutionary Computation | https://www.talkorigins.org/faqs/genalg/genalg.html |
| Convex Optimization | https://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf |
| Data Analysis with Python and PySpark | https://www.manning.com/books/data-analysis-with-python-and-pyspark |
| R for Data Science | https://r4ds.had.co.nz/ |
| Build a Career in Data Science | https://www.manning.com/books/build-a-career-in-data-science |
| Machine Learning Bookcamp | https://mlbookcamp.com/ |
| Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition | https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/ |
| Effective Data Science Infrastructure | https://www.manning.com/books/effective-data-science-infrastructure |
| Practical MLOps: How to Get Ready for Production Models | https://valohai.com/mlops-ebook/ |
| Data Analysis with Python and PySpark | https://www.manning.com/books/data-analysis-with-python-and-pyspark |
| Regression, a Friendly guide | https://www.manning.com/books/regression-a-friendly-guide |
| Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing | https://www.oreilly.com/library/view/streaming-systems/9781491983867/ |
| Data Science at the Command Line: Facing the Future with Time-Tested Tools | https://www.oreilly.com/library/view/data-science-at/9781491947845/ |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#bloggers |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| Wes McKinney | https://wesmckinney.com/archives.html |
| Matthew Russell | https://miningthesocialweb.com/ |
| Vamshi Ambati | https://allthingsds.wordpress.com/ |
| Prash Chan | https://www.mdmgeek.com/ |
| Clare Corthell | https://datasciencemasters.org/ |
| Paul Miller | https://cloudofdata.com/ |
| Data Science London | https://datasciencelondon.org/ |
| Datawrangling | https://datawrangling.com/ |
| Quora Data Science | https://www.quora.com/topic/Data-Science |
| Siah | https://openresearch.wordpress.com/ |
| Data Science Report | https://datasciencereport.com/ |
| Louis Dorard | https://www.ownml.co/blog/ |
| Machine Learning Mastery | https://machinelearningmastery.com/ |
| Daniel Forsyth | https://www.danielforsyth.me/ |
| Data Science Weekly | https://www.datascienceweekly.org/ |
| Revolution Analytics | https://blog.revolutionanalytics.com/ |
| R Bloggers | https://www.r-bloggers.com/ |
| The Practical Quant | https://practicalquant.blogspot.com/ |
| Datascope Analytics | https://datascopeanalytics.com/ |
| Yet Another Data Blog | https://yet-another-data-blog.blogspot.com/ |
| Spenczar | https://spenczar.com/ |
| KD Nuggets | https://www.kdnuggets.com/ |
| Meta Brown | https://www.metabrown.com/blog/ |
| Data Scientist | https://datascientists.net/ |
| WhatSTheBigData | https://whatsthebigdata.com/ |
| Tevfik Kosar | https://magnus-notitia.blogspot.com/ |
| New Data Scientist | https://newdatascientist.blogspot.com/ |
| Harvard Data Science | https://harvarddatascience.com/ |
| Data Science 101 | https://101.datascience.community/ |
| Kaggle Past Solutions | https://www.chioka.in/kaggle-competition-solutions/ |
| DataScientistJourney | https://datascientistjourney.wordpress.com/category/data-science/ |
| NYC Taxi Visualization Blog | https://chriswhong.github.io/nyctaxi/ |
| Learning Lover | https://learninglover.com/blog/ |
| Dataists | https://www.dataists.com/ |
| Data-Mania | https://www.data-mania.com/ |
| Data-Magnum | https://data-magnum.com/ |
| Map Reduce Blog | https://www.mapr.com/blog |
| P-value | https://www.p-value.info/ |
| datascopeanalytics | https://datascopeanalytics.com/blog/ |
| Digital transformation | https://tarrysingh.com/ |
| datascientistjourney | https://datascientistjourney.wordpress.com/category/data-science/ |
| Data Mania Blog | https://www.data-mania.com/blog/ |
| The File Drawer | https://chris-said.io/ |
| Emilio Ferrara's web page | https://www.emilio.ferrara.name/ |
| DataNews | https://datanews.tumblr.com/ |
| Reddit TextMining | https://www.reddit.com/r/textdatamining/ |
| Periscopic | https://periscopic.com/#!/news |
| Hilary Parker | https://hilaryparker.com/ |
| Data Stories | https://datastori.es/ |
| Data Science Lab | https://datasciencelab.wordpress.com/ |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#facebook-accounts |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| Data | https://www.facebook.com/data |
| Big Data Scientist | https://www.facebook.com/Bigdatascientist |
| Data Science Day | https://www.facebook.com/datascienceday/ |
| Data Science Academy | https://www.facebook.com/nycdatascience |
| Facebook Data Science Page | https://www.facebook.com/pages/Data-science/431299473579193?ref=br_rs |
| Data Science London | https://www.facebook.com/pages/Data-Science-London/226174337471513 |
| Data Science Technology and Corporation | https://www.facebook.com/DataScienceTechnologyCorporation?ref=br_rs |
| Data Science - Closed Group | https://www.facebook.com/groups/1394010454157077/?ref=br_rs |
| Center for Data Science | https://www.facebook.com/centerdatasciences?ref=br_rs |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#twitter-accounts |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| Big Data Combine | https://twitter.com/BigDataCombine |
| Big Data Science | https://twitter.com/analyticbridge |
| Chris Said | https://twitter.com/Chris_Said |
| Clare Corthell | https://twitter.com/clarecorthell |
| DADI Charles-Abner | https://twitter.com/DadiCharles |
| Data Science Central | https://twitter.com/DataScienceCtrl |
| Data Science London | https://twitter.com/ds_ldn |
| Data Science Renee | https://twitter.com/BecomingDataSci |
| Data Science Report | https://twitter.com/TedOBrien93 |
| Data Science Tips | https://twitter.com/datasciencetips |
| Data Vizzard | https://twitter.com/DataVisualizati |
| DataScienceX | https://twitter.com/DataScienceX |
| DJ Patil | https://twitter.com/dpatil |
| Domino Data Lab | https://twitter.com/DominoDataLab |
| Drew Conway | https://twitter.com/drewconway |
| Erin Bartolo | https://twitter.com/erinbartolo |
| Greg Reda | https://twitter.com/gjreda |
| Gregory Piatetsky | https://twitter.com/kdnuggets |
| Hadley Wickham | https://twitter.com/hadleywickham |
| Hakan Kardas | https://twitter.com/hakan_kardes |
| Hilary Mason | https://twitter.com/hmason |
| Jeff Hammerbacher | https://twitter.com/hackingdata |
| John Myles White | https://twitter.com/johnmyleswhite |
| Juan Miguel Lavista | https://twitter.com/BDataScientist |
| Julia Evans | https://twitter.com/b0rk |
| Kenneth Cukier | https://twitter.com/kncukier |
| http://www.big-data-book.com/ | http://www.big-data-book.com/ |
| https://www.meetup.com/San-Diego-Data-Science-R-Users-Group/ | https://www.meetup.com/San-Diego-Data-Science-R-Users-Group/ |
| Kevin Markham | https://twitter.com/justmarkham |
| Data School | https://www.dataschool.io/ |
| Kim Rees | https://twitter.com/krees |
| Kirk Borne | https://twitter.com/KirkDBorne |
| Luis Rei | https://twitter.com/lmrei |
| Matt Harrison | https://twitter.com/__mharrison__ |
| Matthew Russell | https://twitter.com/ptwobrussell |
| Mert Nuhoğlu | https://twitter.com/mertnuhoglu |
| Monica Rogati | https://twitter.com/mrogati |
| Noah Iliinsky | https://twitter.com/noahi |
| https://www.oreilly.com/pub/au/4419 | https://www.oreilly.com/pub/au/4419 |
| Paul Miller | https://twitter.com/PaulMiller |
| Peter Skomoroch | https://twitter.com/peteskomoroch |
| Prash Chan | https://twitter.com/MDMGeek |
| Quora Data Science | https://twitter.com/q_datascience |
| R-Bloggers | https://twitter.com/Rbloggers |
| Rand Hindi | https://twitter.com/randhindi |
| Randy Olson | https://twitter.com/randal_olson |
| Recep Erol | https://twitter.com/EROLRecep |
| Ryan Orban | https://twitter.com/ryanorban |
| Sean J. Taylor | https://twitter.com/seanjtaylor |
| Silvia K. Spiva | https://twitter.com/silviakspiva |
| Harsh B. Gupta | https://twitter.com/harshbg |
| Spencer Nelson | https://twitter.com/spenczar_n |
| Talha Oz | https://twitter.com/tozCSS |
| Tasos Skarlatidis | https://twitter.com/anskarl |
| Terry Timko | https://twitter.com/Terry_Timko |
| Tony Baer | https://twitter.com/TonyBaer |
| Tony Ojeda | https://twitter.com/tonyojeda3 |
| Vamshi Ambati | https://twitter.com/vambati |
| https://allthingsds.wordpress.com | https://allthingsds.wordpress.com |
| Wes McKinney | https://twitter.com/wesmckinn |
| WileyEd | https://twitter.com/WileyEd |
| WNYC Data News Team | https://twitter.com/datanews |
| Alexey Grigorev | https://twitter.com/Al_Grigor |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#newsletters |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| AI Digest | https://aidigest.net/ |
| Archive | https://aidigest.net/digests |
| DataTalks.Club | https://datatalks.club |
| Archive | https://us19.campaign-archive.com/home/?u=0d7822ab98152f5afc118c176&id=97178021aa |
| The Analytics Engineering Roundup | https://roundup.getdbt.com/about |
| Archive | https://roundup.getdbt.com/archive |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#youtube-videos--channels |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| What is machine learning? | https://www.youtube.com/watch?v=WXHM_i-fgGo |
| Andrew Ng: Deep Learning, Self-Taught Learning and Unsupervised Feature Learning | https://www.youtube.com/watch?v=n1ViNeWhC24 |
| Data36 - Data Science for Beginners by Tomi Mester | https://www.youtube.com/c/TomiMesterData36comDataScienceForBeginners |
| Deep Learning: Intelligence from Big Data | https://www.youtube.com/watch?v=czLI3oLDe8M |
| Interview with Google's AI and Deep Learning 'Godfather' Geoffrey Hinton | https://www.youtube.com/watch?v=1Wp3IIpssEc |
| Introduction to Deep Learning with Python | https://www.youtube.com/watch?v=S75EdAcXHKk |
| What is machine learning, and how does it work? | https://www.youtube.com/watch?v=elojMnjn4kk |
| Data School | https://www.youtube.com/channel/UCnVzApLJE2ljPZSeQylSEyg |
| Neural Nets for Newbies by Melanie Warrick (May 2015) | https://www.youtube.com/watch?v=Cu6A96TUy_o |
| Neural Networks video series by Hugo Larochelle | https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH |
| Google DeepMind co-founder Shane Legg - Machine Super Intelligence | https://www.youtube.com/watch?v=evNCyRL3DOU |
| Data Science Primer | https://www.youtube.com/watch?v=cHzvYxBN9Ls&list=PLPqVjP3T4RIRsjaW07zoGzH-Z4dBACpxY |
| Data Science with Genetic Algorithms | https://www.youtube.com/watch?v=lpD38NxTOnk |
| Data Science for Beginners | https://www.youtube.com/playlist?list=PL2zq7klxX5ATMsmyRazei7ZXkP1GHt-vs |
| DataTalks.Club | https://www.youtube.com/channel/UCDvErgK0j5ur3aLgn6U-LqQ |
| Mildlyoverfitted - Tutorials on intermediate ML/DL topics | https://www.youtube.com/channel/UCYBSjwkGTK06NnDnFsOcR7g |
| mlops.community - Interviews of industry experts about production ML | https://www.youtube.com/channel/UCYBSjwkGTK06NnDnFsOcR7g |
| ML Street Talk - Unabashedly technical and non-commercial, so you will hear no annoying pitches. | https://www.youtube.com/c/machinelearningstreettalk |
| Neural networks by 3Blue1Brown | https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi |
| Neural networks from scratch by Sentdex | https://www.youtube.com/playlist?list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3 |
| Manning Publications YouTube channel | https://www.youtube.com/c/ManningPublications/featured |
| Ask Dr Chong: How to Lead in Data Science - Part 1 | https://youtu.be/JYuQZii5o58 |
| Regression Models: Applying simple Poisson regression | https://www.youtube.com/watch?v=9Hk8K8jhiOo |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#slack-communities |
| top | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#skunks-skool |
| DataTalks.Club | https://datatalks.club |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#github-groups |
| Berkeley Institute for Data Science | https://github.com/BIDS |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#competitions |
| Kaggle | https://www.kaggle.com/ |
| DrivenData | https://www.drivendata.org/ |
| Analytics Vidhya | https://datahack.analyticsvidhya.com/ |
| InnoCentive | https://www.innocentive.com/ |
| TuneedIT | https://tunedit.org/challenges |
| Microprediction | https://www.microprediction.com/python-1 |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#fun |
| Infographic | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#infographic |
| Data Sets | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#data-sets |
| Comics | https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#comics |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#data-sets |
| Academic Torrents | https://academictorrents.com/ |
| hadoopilluminated.com | https://hadoopilluminated.com/hadoop_illuminated/Public_Bigdata_Sets.html |
| data.gov | https://catalog.data.gov/dataset |
| United States Census Bureau | https://www.census.gov/ |
| usgovxml.com | https://usgovxml.com/ |
| enigma.com | https://enigma.com/ |
| datahub.io | https://datahub.io/ |
| aws.amazon.com/datasets | https://aws.amazon.com/datasets/ |
| datacite.org | https://datacite.org/ |
| The official portal for European data | https://data.europa.eu/en |
| quandl.com | https://www.quandl.com/ |
| figshare.com | https://figshare.com/ |
| GeoLite Legacy Downloadable Databases | https://dev.maxmind.com/geoip |
| Quora's Big Datasets Answer | https://www.quora.com/Where-can-I-find-large-datasets-open-to-the-public |
| Public Big Data Sets | https://hadoopilluminated.com/hadoop_illuminated/Public_Bigdata_Sets.html |
| Kaggle Datasets | https://www.kaggle.com/datasets |
| A Deep Catalog of Human Genetic Variation | https://www.internationalgenome.org/data |
| A community-curated database of well-known people, places, and things | https://developers.google.com/freebase/ |
| Google Public Data | https://www.google.com/publicdata/directory |
| World Bank Data | https://data.worldbank.org/ |
| NYC Taxi data | https://chriswhong.github.io/nyctaxi/ |
| Open Data Philly | https://www.opendataphilly.org/ |
| grouplens.org | https://grouplens.org/datasets/ |
| UC Irvine Machine Learning Repository | https://archive.ics.uci.edu/ml/ |
| research-quality data sets | https://web.archive.org/web/20150320022752/https://bitly.com/bundles/hmason/1 |
| Hilary Mason | https://web.archive.org/web/20150501033715/https://bitly.com/u/hmason/bundles |
| National Climatic Data Center - NOAA | https://www.ncdc.noaa.gov/ |
| ClimateData.us | https://www.climatedata.us/ |
| U.S. Climate Resilience Toolkit | https://toolkit.climate.gov/ |
| r/datasets | https://www.reddit.com/r/datasets/ |
| MapLight | https://www.maplight.org/data-series |
| GHDx | https://ghdx.healthdata.org/ |
| St. Louis Federal Reserve Economic Data - FRED | https://fred.stlouisfed.org/ |
| New Zealand Institute of Economic Research – Data1850 | https://data1850.nz/ |
| Open Data Sources | https://github.com/datasciencemasters/data |
| UNICEF Data | https://data.unicef.org/ |
| undata | https://data.un.org/ |
| NASA SocioEconomic Data and Applications Center - SEDAC | https://sedac.ciesin.columbia.edu/ |
| The GDELT Project | https://www.gdeltproject.org/ |
| Sweden, Statistics | https://www.scb.se/en/ |
| Github free data source list | https://www.datasciencecentral.com/profiles/blogs/great-github-list-of-public-data-sets |
| StackExchange Data Explorer | https://data.stackexchange.com |
| SocialGrep | https://socialgrep.com/datasets |
| San Fransisco Government Open Data | https://datasf.org/opendata/ |
| IBM Blog about open data | https://www.datasciencecentral.com/profiles/blogs/the-free-big-data-sources-everyone-should-know |
| IBM Asset Dataset | https://developer.ibm.com/exchanges/data/ |
| Open data Index | https://index.okfn.org/ |
| Public Git Archive | https://github.com/src-d/datasets/tree/master/PublicGitArchive |
| GHTorrent | https://ghtorrent.org/ |
| Microsoft Research Open Data | https://msropendata.com/ |
| Open Government Data Platform India | https://data.gov.in/ |
| Google Dataset Search (beta) | https://datasetsearch.research.google.com/ |
| NAYN.CO Turkish News with categories | https://github.com/naynco/nayn.data |
| Covid-19 | https://github.com/datasets/covid-19 |
| Covid-19 Google | https://github.com/google-research/open-covid-19-data |
| Enron Email Dataset | https://www.cs.cmu.edu/~./enron/ |
| 5000 Images of Clothes | https://github.com/alexeygrigorev/clothing-dataset |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#comics |
| Comic compilation | https://medium.com/@nikhil_garg/a-compilation-of-comics-explaining-statistics-data-science-and-machine-learning-eeefbae91277 |
| Cartoons | https://www.kdnuggets.com/websites/cartoons.html |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#awesome-lists |
| awesome-awesomeness | https://github.com/bayandin/awesome-awesomeness |
| Awesome Machine Learning | https://github.com/josephmisiti/awesome-machine-learning |
| lists | https://github.com/jnv/lists |
| awesome-dataviz | https://github.com/javierluraschi/awesome-dataviz |
| awesome-python | https://github.com/vinta/awesome-python |
| Data Science IPython Notebooks. | https://github.com/donnemartin/data-science-ipython-notebooks |
| awesome-r | https://github.com/qinwf/awesome-R |
| awesome-datasets | https://github.com/awesomedata/awesome-public-datasets |
| awesome-Machine Learning & Deep Learning Tutorials | https://github.com/ujjwalkarn/Machine-Learning-Tutorials/blob/master/README.md |
| Awesome Data Science Ideas | https://github.com/JosPolfliet/awesome-ai-usecases |
| Machine Learning for Software Engineers | https://github.com/ZuzooVn/machine-learning-for-software-engineers |
| Community Curated Data Science Resources | https://hackr.io/tutorials/learn-data-science |
| Awesome Machine Learning On Source Code | https://github.com/src-d/awesome-machine-learning-on-source-code |
| Awesome Community Detection | https://github.com/benedekrozemberczki/awesome-community-detection |
| Awesome Graph Classification | https://github.com/benedekrozemberczki/awesome-graph-classification |
| Awesome Decision Tree Papers | https://github.com/benedekrozemberczki/awesome-decision-tree-papers |
| Awesome Fraud Detection Papers | https://github.com/benedekrozemberczki/awesome-fraud-detection-papers |
| Awesome Gradient Boosting Papers | https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers |
| Awesome Computer Vision Models | https://github.com/nerox8664/awesome-computer-vision-models |
| Awesome Monte Carlo Tree Search | https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers |
| Glossary of common statistics and ML terms | https://www.analyticsvidhya.com/glossary-of-common-statistics-and-machine-learning-terms/ |
| 100 NLP Papers | https://github.com/mhagiwara/100-nlp-papers |
| Awesome Game Datasets | https://github.com/leomaurodesenv/game-datasets#readme |
| Data Science Interviews Questions | https://github.com/alexeygrigorev/data-science-interviews |
| Awesome Explainable Graph Reasoning | https://github.com/AstraZeneca/awesome-explainable-graph-reasoning |
| Top Data Science Interview Questions | https://www.interviewbit.com/data-science-interview-questions/ |
| Awesome Drug Synergy, Interaction and Polypharmacy Prediction | https://github.com/AstraZeneca/awesome-drug-pair-scoring |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#data-science-communities |
| IBM Data Science Community | https://community.ibm.com/community/user/datascience/home |
| Data Science Central | https://www.datasciencecentral.com/ |
| DataQuest | https://www.dataquest.io/ |
| DrivenData | https://www.drivendata.org/ |
| Data Science Society | https://www.datasciencesociety.net/ |
| Reddit-Data Science | https://www.reddit.com/r/datascience/ |
| https://patch-diff.githubusercontent.com/aiskunks/Skunks_Skool#algorithm-communities |
| Commonlounge Algorithm Community | https://www.commonlounge.com/community/919705a0927646f9b49853ba13793b36 |
| Hackr.io Algorithm Tutorials | https://hackr.io/tutorials/learn-data-structures-algorithms |
| Youth4Work Alogrithm Forum | https://www.youth4work.com/Talent/Data-Structure/Forum |
| 3Blue1Brown | https://www.3blue1brown.com/ |
| quantconnect | https://www.quantconnect.com/forum/discussions/1/interesting |
| codeproject | https://www.codeproject.com/Forums/326859/Algorithms |
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| Community | https://github.community/ |
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