Filter by
The language used throughout the course, in both instruction and assessments.
Results for "support+vector+machine+(svm)"
Status: FreeDeepLearning.AI
Alberta Machine Intelligence Institute
Skills you'll gain: Machine Learning, Human Learning
Skills you'll gain: Leadership and Management, Data Management, Databases, Strategy, Business Analysis, Google Cloud Platform, Machine Learning
Skills you'll gain: Machine Learning, Human Learning, Deep Learning
Wesleyan University
Skills you'll gain: Human Learning, Machine Learning
Skills you'll gain: Databases
MathWorks
Skills you'll gain: Computer Vision, Machine Learning
University of Washington
Skills you'll gain: Machine Learning, Machine Learning Algorithms, Algorithms, Human Learning, Applied Machine Learning, Probability & Statistics, Statistical Machine Learning, Decision Making, Python Programming, Probability Distribution
Coursera Project Network
Skills you'll gain: Data Mining, Deep Learning, Machine Learning, Python Programming
Johns Hopkins University
Skills you'll gain: General Statistics, Probability & Statistics, Linear Algebra, Mathematics, Algebra, Regression
DeepLearning.AI
Skills you'll gain: Machine Learning, Machine Learning Algorithms, Probability & Statistics, Deep Learning
Coursera Project Network
Skills you'll gain: Machine Learning, Python Programming
In summary, here are 10 of our most popular support+vector+machine+(svm) courses
- Vector Databases: from Embeddings to Applications:Â DeepLearning.AI
- Optimizing Machine Learning Performance:Â Alberta Machine Intelligence Institute
- How Google does Machine Learning em Português Brasileiro: Google Cloud
- Practical Machine Learning on H2O:Â H2O.ai
- Machine Learning for Data Analysis:Â Wesleyan University
- Learn Embeddings and Vector Databases:Â Scrimba
- Machine Learning for Computer Vision:Â MathWorks
- Machine Learning: Classification:Â University of Washington
- Mining Quality Prediction Using Machine & Deep Learning:Â Coursera Project Network
- Advanced Linear Models for Data Science 2: Statistical Linear Models:Â Johns Hopkins University
