Monthly Archives: February 2017

The Bias v.s. Variance Tradeoff

All posts in the series:

  1. Linear Regression
  2. Logistic Regression
  3. Neural Networks
  4. The Bias v.s. Variance Tradeoff
  5. Support Vector Machines
  6. K-means Clustering
  7. Dimensionality Reduction and Recommender Systems
  8. Principal Component Analysis
  9. Recommendation Engines

Here my pythonic playground about Bias v.s Variance in Machine Learning.
The code below was originally written in matlab for the programming assignments of Andrew Ng’s Machine Learning course on Coursera.
I had some fun translating everything into python!
Find the full code here on Github and the nbviewer version here.

by Francesco Pochetti

Pythonic Neural Networks

All posts in the series:

  1. Linear Regression
  2. Logistic Regression
  3. Neural Networks
  4. The Bias v.s. Variance Tradeoff
  5. Support Vector Machines
  6. K-means Clustering
  7. Dimensionality Reduction and Recommender Systems
  8. Principal Component Analysis
  9. Recommendation Engines

Here my implementation of Neural Networks in numpy.
The code below was originally written in matlab for the programming assignments of Andrew Ng’s Machine Learning course on Coursera.
I had some fun translating everything into python!
Find the full code here on Github and the nbviewer version here.

by Francesco Pochetti