Роман с Data Science. Как монетизировать большие данные

55. Introduction to Machine Learning. Second Edition. Ethem Alpaydin.

56. Scikit learn Ensemble methods. https://scikit-learn.org/stable/modules/ensemble.html

57. XGBoost: Introduction to Boosted Trees. https://xgboost.readthedocs.io/en/latest/tutorials/model.html

58. LightGBM. https://lightgbm.readthedocs.io/

59. Catboost. https://catboost.ai/

60. Andrew Ng. Machine learning Yearning.

61. Coursera Machine Learning. https://www.coursera.org/learn/machine-learning

62. How do I learn machine learning? https://qr.ae/pN9vA4

63. Fastml4j on Scala. https://github.com/rzykov/fastml4j

64. Netflix prize. https://www.netflixprize.com

65. Netflix Recommendations: Beyond the 5 stars (Part 1). https://netflixtechblog.com/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429

66. Andrew Gelman, Jenifer Hill «Data Analysis Using Regression and Multilevel/Hierarchical Models». https://www.dropbox.com/s/a82wwn6l74j5qka/Gelman-missing.pdf?dl=0

67. Google Course of ML: Imbalanced Data. https://developers.google.com/machine-learning/data-prep/construct/sampling-splitting/imbalanced-data

68. «10 уроков рекомендательной системы Quora». https://habr.com/ru/company/retailrocket/blog/341346/

69. «Как разрушился стартап, годами выдававший армию бухгалтеров за искусственный интеллект». https://www.forbes.ru/tehnologii/405589-kak-razrushilsya-startap-godami-vydavavshiy-armiyu-buhgalterov-za-iskusstvennyy

70. Yandex Toloka. https://toloka.ai/ru/

71. Drilling Down: Turning Customer Data into Profits with a Spreadsheet – Third Edition, Jim Novo.

72. Google Rules of Machine Learning: Best Practices for ML Engineering. https://developers.google.com/machine-learning/guides/rules-of-ml

73. В Норвегии с паразитами рыб борются при помощи подводных роботов с лазерами. https://habr.com/ru/post/402797/

74. «Русская аквакультура» взялась за разведение лосося на Дальнем Востоке. https://www.rbc.ru/business/01/09/2020/5f4cb2159a7947347c5c16a9

75. Adidas backpedals on robotic shoe production with Speedfactory closures. https://techcrunch.com/2019/11/11/adidas-backpedals-on-robotic-factories/

76. Рохо, Антонио. Возможно да, возможно нет. Фишер. Статистический вывод // Наука. Величайшие теории. – М.: Де Агостини, 2015. – Вып. 47. – ISSN 2409–0069.

77. Larry Wasserman, All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics), Springer (December 1, 2010).

78. Непараметрические критерии. http://statistica.ru/theory/neparametricheskie-kriterii/

79. B. Efron, Bootstrap Methods: Another Look at the Jackknife.https://doi.org/10.1214/aos/1176344552

80. Bootstrap confidence intervals. https://www.dropbox.com/s/6dbqxrcocmfxyvp/MIT18_05S14_Reading24.pdf?dl=0

81. Criteo Labs: Why your A/B-test needs confidence intervals. https://medium.com/criteo-labs/why-your-ab-test-needs-confidence-intervals-bec9fe18db41

82. Bayesian A/B tests. https://richrelevance.com/2013/05/21/bayesian-ab-tests/

83. William Bolstard, Introduction to Bayesian Statistics.

84. Ron Kohavi, Alex Deng, Roger Longbotham, and Ya Xu. Seven Rules of Thumb for Web Site Experimenters. https://exp-platform.com/rules-of-thumb/

85. Retail Rocket Segmentator. https://github.com/RetailRocket/RetailRocket.Segmentator

86. Reinforcement Learning: An Introduction. https://web.stanford.edu/class/psych209/Readings/SuttonBartoIPRLBook2ndEd.pdf

87. The Privacy Project. https://www.nytimes.com/interactive/2019/opinion/internet-privacy-project.html

88. One Nation tracked. https://www.nytimes.com/interactive/2019/12/19/opinion/location-tracking-cell-phone.html

89. Google Authorized Buyers, Real-time Bidding. https://developers.google.com/authorized-buyers/rtb/start

90. Explained: Data in the Criteo Engine. https://www.criteo.com/blog/explained-data-in-the-criteo-engine/

91. We Built an ‘Unbelievable’ (but Legal) Facial Recognition Machine. https://www.nytimes.com/interactive/2019/04/16/opinion/facial-recognition-new-york-city.html

92. What ISPs Can See, Upturn, March 2016. https://www.upturn.org/reports/2016/what-isps-can-see/

93. The GDPR Is a Cookie Monster. https://content-na1.emarketer.com/the-gdpr-is-a-cookie-monster

94. IAB. Cookies on Mobile 101. https://www.iab.com/wp-content/uploads/2015/07/CookiesOnMobile101Final.pdf

95. How Online Shopping Makes Suckers of Us All. https://www.theatlantic.com/magazine/archive/2017/05/how-online-shopping-makes-suckers-of-us-all/521448/

96. Почему крупнейшие сайты рунета убирают счетчик Liveinternet? https://vc.ru/flood/1822-pochemu-krupneyshie-saytyi-runeta-ubirayut-schetchik-liveinternet

97. How To Break Anonymity of the Netflix Prize Dataset. https://arxiv.org/abs/cs/0610105

98. ‘Alexa, are you invading my privacy?’ – the dark side of our voice assistants. https://www.theguardian.com/technology/2019/oct/09/alexa-are-you-invading-my-privacy-the-dark-side-of-our-voice-assistants

99. LeakyPick: IoT Audio Spy Detector. https://arxiv.org/abs/2007.00500

100. I Search, Therefore I AM, Andreas Weigend. https://www.dropbox.com/s/xk6w60szuq6dpeh/WeigendFOCUS2004-en.pdf?dl=0