Ask HN: How to get started with machine learning?

I strongly advice for:

- using Python in the interactive environment Jupyter Notebook,

- starting with classical machine learning (scikit-learn), NOT from deep learning; first learn logistic regression (a prerequisite for any neural network), kNN, PCA, Random Forest, t-SNE; concepts like log-loss and (cross-)validation,

- playing with real data,

- it is cool to add neural networks afterwards (here bare TensorFlow is a good choice, but I would suggest Keras).

Links:

- http://www.r2d3.us/visual-intro-to-machine-learning-part-1/

- http://hangtwenty.github.io/dive-into-machine-learning/

- https://github.com/leriomaggio/deep-learning-keras-euroscipy...

1. Machine Learning by Andrew Ng (https://www.coursera.org/learn/machine-learning) /// Class notes: (http://holehouse.org/mlclass/index.html)

2. Yaser Abu-Mostafa’s Machine Learning course which focuses much more on theory than the Coursera class but it is still relevant for beginners.(https://work.caltech.edu/telecourse.html)

3. Neural Networks and Deep Learning (Recommended by Google Brain Team) (http://neuralnetworksanddeeplearning.com/)

4. Probabilistic Graphical Models (https://www.coursera.org/learn/probabilistic-graphical-model...)

4. Computational Neuroscience (https://www.coursera.org/learn/computational-neuroscience)

5. Statistical Machine Learning (http://www.stat.cmu.edu/~larry/=sml/)

If you want to learn AI: https://medium.com/open-intelligence/recommended-resources-f...

http://academictorrents.com/browse.php?search=machine+learni...