Looking for a machine learning algorithms list? Explore key ML models, their types, examples, and how they drive AI and data science advancements in 2025.
Course 2 of 4 in the Machine Learning: Algorithms in the Real World Specialization Syllabus WEEK 1 Classification using Decision Trees and k-NN Welcome to Supervised Learning, Tip to Tail! This week we'll go over the basics of supervised learning, particularly classification, as well as teac...
This equips you with the expertise needed to harness advanced machine-learning algorithms. You will delve into the intricacies of cutting-edge machine-learning algorithms. Complex concepts will be simplified, making them accessible and actionable for you to harness the potential of advanced algorithms ...
scikit-learn A set of python modules for machine learning and data mining 29 urllib3 HTTP library with thread-safe connection pooling, file post, and more. 27 scipy Fundamental algorithms for scientific computing in Python 27 torch Tensors and Dynamic neural networks in Python with strong GPU ac...
OpenAI Gym.A toolkit for developing and comparing reinforcement learning algorithms. #reinforcementlearning #openai #python 2016-04-13 CreativeAi.A space to share research and experiments that deal with Creativity and A.I. #art #ai 2016-04-12 ...
Reinforcement Learning in PyTorch. TensorFlow Reinforcement Learning. A toolkit for developing and comparing reinforcement learning algorithms. 迁移学习 | Transfer Learning 综合 A list of awesome papers and cool resources on transfer learning, domain adaptation and domain-to-domain translation in general. ...
Weka - Weka is a collection of machine learning algorithms for data mining tasks. LBJava - Learning Based Java is a modelling language for the rapid development of software systems, offers a convenient, declarative syntax for classifier and constraint definition directly in terms of the objects in...
Machine learning algorithmsWhen optimizing an multiobjective optimization problem, the evolution of population can be regarded as a approximation to the Pareto ... HL Liu,L Chen,Q Zhang,... - IEEE 被引量: 321发表: 2016年 Multi-Objective Machine Learning Publisher's description: Recently, increas...
fields institute Optimization: Theory, Algorithms, Applications Lecture Series International Conference on Information Geometry for Data Science Institute for Data Science Foundations Blogs machine learning Lil'Log Archive probability: Random Fields Diffusion processes and other random processes. Johannes Kepler ...
Understanding Machine Learning: From Theory to Algorithms Author: Shai Shalev-Shwartz and Shai Ben-David For the mathematics- savvy people, this is one of the most recommended books for understanding the magic behind Machine Learning. Deep Learning Tutorial Author: LISA lab, University of Montreal ...