Tag Archives: SciKit-Learn

Calling Python’s scikit-learn machine learning library from Julia


It turns out to be very easy. Here’s a python code for SVM classification And here’s Julia code – utilizing PyCall module

https://rizalzaf.wordpress.com/2015/05/15/calling-pythons-scikit-learn-machine-learning-library-from-julia/

Video: Setting up Python for machine learning: scikit-learn and IPython Notebook


Want to get started with machine learning in Python? I’ll discuss the pros and cons of the scikit-learn library, show how to install my preferred Python distribution, and demonstrate the basic functionality of the IPython Notebook. If you don’t yet know any Python, I’ll also provide four recommended resources for learning Python.

Video: Unsupervised Machine Learning – Hierarchical Clustering with Mean Shift Scikit-learn and Python


This machine learning tutorial covers unsupervised learning with Hierarchical clustering. This is clustering where we allow the machine to determine how many categories to cluster the unlabeled data into.

sample code: http://pythonprogramming.net

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Video: Unsupervised Machine Learning – Flat Clustering with KMeans with Scikit-learn and Python


This unsupervised machine learning tutorial covers flat clustering, which is where we give the machine an unlabeled data set, and tell it how many categories we want the data categorized into.

sample code: http://pythonprogramming.net

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Video: Scikit Learn Machine Learning Tutorial for investing with Python p. 24


In this machine learning tutorial video, we cover how to improve and raise the standards of companies that we’d like to invest in.

sample code: http://pythonprogramming.net

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SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.


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SKLL (pronounced “skull”) provides a number of utilities to make it simpler to run common scikit-learn experiments with pre-generated features.

There are two primary means of using SKLL: the run_experiment script and the Python API.

Indices and tables