Look at this video from udacity ….it is great:
Look at this video from udacity ….it is great:
This post is a great summary of the bias versus varianve dilemma and how to solve it
https://www.linkedin.com/pulse/6-ways-make-your-predictive-models-better-ahmed-el-deeb
Look at:
https://wiki.python.org/moin/PythonForArtificialIntelligence
and:
This information came from a post of Santiago Egea (Universidad de Valladolid)
To start with deep learning:
http://deeplearning.stanford.edu/
http://ufldl.stanford.edu/tutorial/supervised/ConvolutionalNeuralNetwork/
http://www.cs.toronto.edu/~hinton/
http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial
http://www.quora.com/Whats-the-most-effective-way-to-get-started-with-Deep-Learning
https://www.kaggle.com/c/facial-keypoints-detection/details/deep-learning-tutorial
http://www.kdnuggets.com/2014/05/learn-deep-learning-courses-tutorials-overviews.html
Links to places than explain well how to do PCA and how to understand it…….
New edition coming of:
Mining Massive Datasets from Stanford
On this month starts a new edition of the Statistical Learning course in Stanford on-line:
https://class.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about
and excellent course from Hastie and Tibshirani. The course is based on R.
Here is an excellent list of tools from python that you can use for your machine learning projects:
http://stats.stackexchange.com/questions/1595/python-as-a-statistics-workbench
extracted from this reference:
If speed becomes a problem, consider Theano — used with good success by the deep learning people.
Information for the tools:
For Pandas:
http://pandas.pydata.org/pandas-docs/dev/10min.html
for a short summary on pandas:
For Numpy/Scipy:
http://wiki.scipy.org/Cookbook
For GLM:
http://statsmodels.sourceforge.net/devel/examples/notebooks/generated/glm.html
Monte Carlo
Excellent follow up courses on machine learning
http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml … Carnegie Mellon, Tom Mitchell
.. Andrew Ng CS 229 , it is diferent and more advanced than the coursera course by Ng
http://cs229.stanford.edu/materials.html
Machine Learning by Pedro Gomingos, University of Wasington
Complete list of machine learning courses online: