{"id":21748349,"url":"https://github.com/surfstudio/mlcandidatepath","last_synced_at":"2025-03-21T02:25:10.987Z","repository":{"id":71210879,"uuid":"87568452","full_name":"surfstudio/MLCandidatePath","owner":"surfstudio","description":null,"archived":false,"fork":false,"pushed_at":"2019-04-09T10:39:02.000Z","size":12,"stargazers_count":22,"open_issues_count":0,"forks_count":9,"subscribers_count":10,"default_branch":"master","last_synced_at":"2025-01-25T22:57:55.243Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/surfstudio.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-04-07T17:02:00.000Z","updated_at":"2024-06-17T08:35:44.000Z","dependencies_parsed_at":"2023-03-30T11:38:07.658Z","dependency_job_id":null,"html_url":"https://github.com/surfstudio/MLCandidatePath","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surfstudio%2FMLCandidatePath","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surfstudio%2FMLCandidatePath/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surfstudio%2FMLCandidatePath/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surfstudio%2FMLCandidatePath/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/surfstudio","download_url":"https://codeload.github.com/surfstudio/MLCandidatePath/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244723747,"owners_count":20499326,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-26T08:13:09.322Z","updated_at":"2025-03-21T02:25:10.978Z","avatar_url":"https://github.com/surfstudio.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Путь Тони Старка в машинном обучении\n\nПара слов о том, как читать этот список и выбирать из него материалы.\n\nНа данный момент Surf специализируется в своих разработках на 3 основных направлениях:\n\n- Классическое машинное обучение (Machine Learning)\n- Рекомендальные системы (Recommender Systems)\n- Глубокое обучение (Deep Learning)\n\nМы _очень иногда_ занимаемся обработкой естественных языков (Natural Language Processing) и _не_ занимаемся обучением с подкреплением (Reinforcement Learning). Также у нас нет предсказаний в области спорта, цен акций или курса валют или металлов. Только классические задачи.\n\nПоэтому ваши знания будут ранжированы нам согласно нашему профилю.\n\n------\n\n* ✅ - желательно, чтобы знал(-а)\n* ➕ - будет плюсом, но не обязательно\n* 🍒 - тоже хорошая вещь, но вряд ли пригодится в работе\n\n## Повторить математику\n* ✅ http://students.brown.edu/seeing-theory/ - Тервер, матстат\n* ✅ https://stepik.org/course/Основы-статистики-76/ - Матстат\n* ✅ https://sites.google.com/site/butwhymath/ - Алгебра, диф.исчисление, комплексные числа, Фурье\n* ✅ http://immersivemath.com/ila/index.html - Линал\n* ✅ https://stepik.org/course/Дискретные-структуры-83/syllabus - Дискретка\n* ➕ https://www.khanacademy.org/math - Всё\n\n## Основы машинного обучения\n* ✅ https://www.coursera.org/learn/machine-learning - Классический курс от Andrew Ng\n* ➕ https://www.coursera.org/specializations/machine-learning-data-analysis - Специализация от Яндекса и МФТИ\n* ➕ http://wiki.cs.hse.ru/Машинное_обучение_1 - Курс от ВШЭ\n* 🍒 https://github.com/esokolov/ml-course-msu - Курс от МГУ, много математики\n* ✅ https://www.youtube.com/watch?v=u433nrxdf5k - Лекция по временным рядам\n\n## Глубокое обучение\n\n* ✅ https://dlcourse.ai/ - Русский курс по Deep Learning от Семёна Козлова\n* ➕ https://www.coursera.org/specializations/deep-learning - Мощная и классная специализация по DL, состоящая из 5 курсов\n* ➕ http://cs231n.stanford.edu/syllabus.html - Stanford CS231n\n* 🍒 https://www.fast.ai/2019/01/24/course-v3/ - Practical Deep Learning For Coders\n* 🍒 http://yerevann.com/a-guide-to-deep-learning/ - A Guide to Deep Learning by Yerevann\n\n## Рекомендательные системы\n\n* ➕ https://www.cse.iitk.ac.in/users/nsrivast/HCC/Recommender_systems_handbook.pdf - Recommender Systems\nHandbook (2nd Edition)\n* ➕ https://www.twirpx.com/file/2214444/ - Aggarwal C.C. Recommender Systems: The Textbook\n\n## NLP\n* ➕ http://web.stanford.edu/class/cs224n/ - Stanford CS224n\n* 🍒 https://stepik.org/course/Введение-в-обработку-естественного-языка-1233/syllabus - Введение в обработку естественного языка\n* 🍒 https://nlpub.ru/ - NLPub\n\n## Обучение с подкреплением\n* 🍒 http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html - UCL Course on RL\n* 🍒 http://rll.berkeley.edu/deeprlcourse/#lecture-videos - RL от Berkeley\n* 🍒 https://github.com/yandexdataschool/Practical_RL - RL от ШАДа\n\n## Компиляции\n* ➕ http://homepages.inf.ed.ac.uk/rbf/IAPR/researchers/MLPAGES/mltut.htm\n* 🍒 https://github.com/ChristosChristofidis/awesome-deep-learning - Awesome Deep Learning\n\n## Книги\n\n* ✅ https://www.ozon.ru/context/detail/id/142987816/?gclid=CjwKCAjwhbHlBRAMEiwAoDA34-kMeeAVz5dgLUPwuQ8_uXSKFQz7A4wyly5GhQ1XGUrwuqJx-lsivhoCV3gQAvD_BwE - Хорошая книжка Николенко по глубокому обучению\n* ✅ [Chollet, Deep Learning with Keras](https://github.com/hktxt/bookshelf/blob/master/Computer%20Science/Deep%20Learning%20with%20Python%2C%20Fran%C3%A7ois%20Chollet.pdf) - Глубокое обучение на примерах, все на Keras\n* ➕ http://www.deeplearningbook.org/ - Deep Learning Book - в начале есть математика, необходимая в работе\n* ➕ https://web.stanford.edu/~hastie/Papers/ESLII.pdf - Elements of Statistical Learning, главы 1-4, 7.\n\n## В конце-концов\n* ✅ http://www.itshared.org/2015/10/data-science-interview-questions.html - Убедись, что на много отсюда сможешь ответить\n* ➕ https://blog.insightdatascience.com/best-practices-for-interviewing-data-science-candidates-823219120b2e - Посмотреть на интервью с нашей стороны\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsurfstudio%2Fmlcandidatepath","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsurfstudio%2Fmlcandidatepath","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsurfstudio%2Fmlcandidatepath/lists"}