Free online
Learn Support Vector Machine online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
Alberta Machine Intelligence Institute
This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally…
This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionalit…
Stanford University
Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in R. Course material updated in 2021 for second edition of the course textbook.
Korea Advanced Institute of Science and Technology(KAIST)
'Learn concept of AI such as machine learning, deep-learning, support vector machine which is related to linear algebra - Learn how to use linear algebra for AI algorithm. - After completing this course, you are able to understand AI algorithm and basics of linear algebra for AI applications.
Stanford University
Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in Python.
00:00:00 - Introduction 00:00:15 - Machine Learning 00:01:15 - Supervised Learning 00:08:11 - Nearest-Neighbor Classification 00:12:30 - Perceptron Learning 00:33:19 - Support Vector Machines 00:39:31 - Regression 00:42:37 - Loss Functions 00:49:33 - Overfitting 00:55:44 - Regularization 00:59:42 -…
University of Colorado Boulder
The "Classification Analysis" course provides you with a comprehensive understanding of one of the fundamental supervised learning methods, classification. You will explore various classifiers, including KNN, decision tree, support vector machine, naive bayes, and logistic regression, and learn how…
Columbia University
Master the essentials of machine learning and algorithms to help improve learning from data without human intervention.
MIT OpenCourseWare
The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empiri…
Udacity
Streamline complex machine learning projects by designing pipelines that combine preprocessing, modeling, and evaluation. Learn to manage numeric, image, and text data efficiently while preventing data leakage and boosting reproducibility.
Great Learning
Support vector machines or support vector networks are models based on supervised learning models that are primarily used for classification and regression analysis. Support vector machine or SVM is a robust and highly efficient prediction method with a firm foundation in statistical methods It was…
University of Colorado Boulder
"Trees, SVM and Unsupervised Learning" is designed to provide working professionals with a solid foundation in support vector machines, neural networks, decision trees, and XG boost. Through in-depth instruction and practical hands-on experience, you will learn how to build powerful predictive mode…
Great Learning
Support Vector Machine is preferred by many as it produces significant accuracy with very little computational power. The Support Vector Machine initially constructs a hyperplane or a set of hyperplanes that are used to divide or separate the different classes. It is called Support Vector Machine a…
MIT OpenCourseWare
Focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. Develops basic tools such as Regularization including Support Vector Machines for regression and classification.…
Northeastern University
This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering…
MIT OpenCourseWare
6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Ma…
In this series, I have covered various Machine learning techniques for beginners. I have tried to cover all the ML Algorithms like linear regression, support vector machines, decision trees including the intricacies like how a linear regression works and how it evaluates loss for getting correct pr…
Northeastern University
This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering…
