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- # Курсы
- ## Курсы, которые надо пройти
- * [Deep Learning Google](https://eu.udacity.com/course/deep-learning--ud730)
- * [Machine Learning Crash Course with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/)
- * [Learning TensorFlow](https://learningtensorflow.com)
- * [Kaggel Learn](https://www.kaggle.com/learn/overview)
- * [Data Vizualization Kaggle](https://www.kaggle.com/learn/data-visualisation)
- * Andrew Ng
- * cs221
- * Future Learning
- * [HSE Course (GitHub)](https://github.com/esokolov/ml-course-hse/)
- ## Stepic Additional
- * [Examination](https://stepik.org/lesson/68008/step/1?unit=44971)
- * [Adaptive tasks](https://stepik.org/lesson/43732/step/1?adaptive=true&unit=22777)
- ## Курсы, что я прохожу
- * ODS ML Course Open
- * Deep NLP MIPT
- * cs224n (NLP)
- ## Курсы, что я уже прошел
- -----
- # Чтение
- ## Штуки, что надо прочитать
- * [How Numba and Cython speed up Python code](https://rushter.com/blog/numba-cython-python-optimization/)
- * [Serving machine learning models with RestServe on R](http://restrserve.org/serving-ml.html)
- * [R TensorFlow Tutorial](https://tensorflow.rstudio.com)
- * [R Keras Tutorial](https://keras.rstudio.com)
- * [New Resources for Deep Learning with the Neuromation Platform](https://medium.com/neuromation-io-blog/new-resources-for-deep-learning-with-the-neuromation-platform-55fd411cb440)
- * [Word2Vec Tutorial](http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/)
- * [Серия статей про ембединги текста](http://ruder.io/word-embeddings-1/)
- * [ImageNet Classification with Deep Convolutional Neural Networks - Colyer](https://blog.acolyer.org/2016/04/20/imagenet-classification-with-deep-convolutional-neural-networks/)
- * [Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition](https://blog.acolyer.org/2016/04/19/context-dependent-pre-trained-deep-neural-networks-for-large-vocabulary-speech-recognition/)
- https://habrahabr.ru/post/352632/ Истинная реализация нейросети с нуля.
- -----
- # Видео
- ## Штуки, что я прочитал
- ## Видео, что мне надо посмотреть
- * [Essense of Linear Azlgebra](https://www.youtube.com/watch?v=kjBOesZCoqc&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
- * [PyData Meetup (TensorFlow Architecture)](https://www.youtube.com/watch?v=aoin1nl_eSA&feature=youtu.be&t=5810) [Materials](https://github.com/yurijvolkov/pydata_examples)
- * [Kaggle Mercedes Benz: предсказание времени тестирования автомобилей ](https://www.youtube.com/watch?v=HT3QpRp2ewA)
- * [Эффективные модели ближайших соседей](https://www.youtube.com/watch?v=UUm4MOyVTnE)
- ## Видео, что я посмотрел
- * [NLP натекин](https://www.youtube.com/watch?v=Ozm0bEi5KaI)
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