General Machine Learning Notes

Learning Machine Learning
- ML courses from Yandex: Машинное обучение и анализ данных
- Big Data for Data Engineers Specialization
Learning Deep Learning
Recommendations for Learning Recommender Systems
- Recommender Systems Specialization
- Recommender Systems Handbook, 2nd edition
Python libs

Learning Machine Learning ¶

ML courses from Yandex: Машинное обучение и анализ данных ¶

https://www.coursera.org/specializations/machine-learning-data-analysis

A set of good introductory courses for diving into the topic. In Russian.

Note that, as with most of Coursera courses, you can audit all the courses from this specialization. You won’t get the certificate and won’t be able to submit the practical assignments, but you’ll all the videos and materials – for free.

Big Data for Data Engineers Specialization ¶

https://www.coursera.org/specializations/big-data-engineering

Learning Deep Learning ¶

Stanford CS231n: Convolutional Neural Networks for Visual Recognition ¶

Good deep learning course from Stanford University. Really nice practical tasks. The best back propogation explanation ever.

The YouTube link above is not the latest one, it’s from 2016 where it was mostly read by Andrej Karpathy, who is very cool. You can find 2017 videos on the net, but the updates are not very significant.

Standford CS224n: Natural Language Processing with Deep Learning ¶

The title says it all. Not bad.

Deep Learning specialization from deeplearning.ai ¶

https://www.coursera.org/specializations/deep-learning

I did not look at it, but it must be good: the primary author is Andrew Ng.

Advanced Machine Learning, from Yandex and HSE ¶

https://www.coursera.org/specializations/aml

Pretty ok set of courses. Videos are, in my opinion, too terse, but practical tasks are nice. Includes the famous course “How to Win a Data Science Competition: Learn from Top Kagglers”.

Book: Neural Networks and Deep Learning ¶

http://neuralnetworksanddeeplearning.com

Book: Deep learning book ¶

http://www.deeplearningbook.org/

Recommendations for Learning Recommender Systems ¶

Recommender Systems Specialization ¶

https://www.coursera.org/specializations/recommender-systems

Recommender Systems Handbook, 2nd edition ¶

http://www.springer.com/gp/book/9781489976369

Python libs ¶

General stuff:

conda install future
pip install hacking
pip install opencv-python

ML-related:

pip install kaggle
pip install xgboost
pip install lightgbm
pip install scikits.bootstrap
pip install scikit-optimize

Neural networks:

conda install numpy --upgrade  # for TF
# check for the latest version
pip install 'https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.5.0-cp36-cp36m-linux_x86_64.whl'
pip install keras
conda install pytorch-cpu torchvision -c pytorch

Notebooks:

conda install tqdm
conda install -c damianavila82 rise
pip install mpld3
conda install bokeh
pip install holoviews