r/MachineLearning - [D] Are we renaming Unsupervised Learning to Self-Supervised Learning?

#artificialintelligence

Self-supervised learning uses way more supervisory signals than supervised learning, and enormously more than reinforcement learning. That's why calling it "unsupervised" is totally misleading. That's also why more knowledge about the structure of the world can be learned through self-supervised learning than from the other two paradigms: the data is unlimited, and amount of feedback provided by each example is huge.


Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning

Neural Information Processing Systems

In PU learning, a binary classifier is trained from positive (P) and unlabeled (U) data without negative (N) data. Although N data is missing, it sometimes outperforms PN learning (i.e., ordinary supervised learning). Hitherto, neither theoretical nor experimental analysis has been given to explain this phenomenon. In this paper, we theoretically compare PU (and NU) learning against PN learning based on the upper bounds on estimation errors. We find simple conditions when PU and NU learning are likely to outperform PN learning, and we prove that, in terms of the upper bounds, either PU or NU learning (depending on the class-prior probability and the sizes of P and N data) given infinite U data will improve on PN learning.


dennybritz/reinforcement-learning

#artificialintelligence

In addition to exercises and solution, each folder also contains a list of learning goals, a brief concept summary, and links to the relevant readings. All code is written in Python 3 and uses RL environments from OpenAI Gym. Advanced techniques use Tensorflow for neural network implementations.


Machine Learning 101-- Supervised Learning

#artificialintelligence

Machine learning is basically teaching computers to solve big problems based on either example data or past experiences. Example data, is purely unlabeled, with unknown and undetected structure. Your power would rely on you guessing the hidden structure which ultimately leads in you learning more about it. Using technical terminologies, unsupervised learning best describes the latter. Past experiences on the other hand, is real data with clear labels and answers to the question you are trying to answer.


Supervised Learning - Comprehensive Tutorial (Python-based)

@machinelearnbot

This article is from Scikits learn. Scikit-learn Machine Learning in Python is simple and efficient tools for data mining and data analysis. You can check all this information, here.