- Using TeX in your post
- A Modification to the Learning Diagram
- Fitting fields/functions with NN
- Machine Learning
- Selecting Data for Training, Testing and Validation
- Support Vector Machines, Kernel Functions, Data Snooping
- Multi-Class Classifier
- AUC Metric
- Data Snooping, Classifiers
- SVM Research
- How to calculate VC dimension for matrix factorization (Netflix-like) tasks
- Types of Machine Learning
- Problem with simple perceptron implmenetation
- Dependent Data
- Normal equation in linear regression
- Spatial visualization in more than 3 dimensions
- Machine learning with vector images
- Congratulations Caltech!
- Signals predict
- computational complexity?
- Weather prediction
- Selecting "representative" test data
- Which kernel to use?
- Regression on hidden variables
- Polynomial regression
- Cross validation and scaling?
- Linear model in lecture 18
- SVM and C-parameter selection
- expected value for the SVM generalization error
- Covariate Shift in Data
- Neural network with discrete and continuous input
- Good Basic Books or courses for a Novice in Machine learining
- Learning Approach vs. Function Approximation
- Parallel machine learning
- Ideas of applications of machine learning in emacs
- How to handle ambiguous target function, f
- When to use normalization?
- General question on sampling bias
- cross validation and feature selection
- Neural Network predictions converging to one value
- How to get into Machine Learning Research
- Statistics vs. Machine Learning
- Machine Learning and census models
- Criss-cross validation
- kpca and svm
- Regression and Classification Problems
- Under-represented class data
- Try this!
- SVMs, kernels and logistic regression
- In-sample error and Max Likelihood
- Feature dimensionality, regularization and generalization
- Follow up reading on ML
- VC dimension of time series models
- Bayesian Model Combination
- ML tutoring help
- 'novel breakthrough theory of machine learning' by Vladimir Vapnik
- Looking for facts extraction tools
- Time Series method similarities
- example non-overlap hypothesis set H to make union bound equals vc bound
- What is the difference between machine learning and Learning from Data?
- The VC dimension, complexity, and hypothesis set
- A general learning problem
- Google TensorFlow has created a visual neural network learning tool
- A Question about machine learning
- Lecture Notes from Information and Complexity?
- Q: MacKay's method of setting weight decay
- How do we account for the grouping of the training data?
- applying machine learning?
- Best site for summary notes for the course!