If you’re interested in learning machine learning but didn’t know where to start – then you’re in luck.
Cornell University’s entire introduction to machine learning course (‘Machine Learning for Intelligent Systems’) taught by professor Kilian Weinberger is now available online on Youtube (for free), covering ‘basic skills to decide which learning algorithm to use for what problem, code up your own learning algorithm and evaluate and debug it’.
Here is the syllabus of free machine learning course as outlined by Cornell university:
- Machine Learning Setup
- k-Nearest Neighbors / Curse of Dimensionality
- Perceptron
- Estimating Probabilities from data
- Bayes Classifier and Naive Bayes
- Logistic Regression / Maximum Likelihood Estimation / Maximum a Posteriori
- Gradient Descent
- Linear Regression
- Support Vector Machine
- Empirical Risk Minimization
- Model Selection
- Bias-Variance Tradeoff
- Kernels
- Kernels continued
- Gaussian Processes
- k-Dimensional Trees
- Decision Trees
- Bagging
- Boosting
- Neural Networks
- Deep Learning / Stochastic Gradient Descent
You can find the full Youtube playlist here. And here is the class homepage that offers additional information on the course as well as lecture notes.
