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Machine Learning and AI: Support Vector Machines in Python is a course in which you learn about artificial intelligence, support vector machines, and data science algorithms in Python, and learn how to classify and regress. The support vector machine is one of the most powerful machine learning models used for classification. Today, talk of deep learning is heard everywhere, and this course tries to teach you valuable material in this field.
One of the problems with the support vector machine is that it is theoretically learned and many students simply ignore it. In this training course, we try to show you with a step-by-step and practical method all the theoretical topics about the support vector machine and how it works. We use logistic regression as a starting point and then teach you other SVM topics.
Apply SVM to applications
Understand support machine vector theory
Work with image recognition, spam detection, and regression analysis software
Build RBF networks and other neural networks
English language
Duration: 8 hours and 50 minutes
Number of courses: 72
Level of education: Intermediate
Instructor: Lazy Programmer Inc
File format: mp4
72 lectures 08:50:20
Welcome 4 lectures 18:51
Beginner’s Corner 7 lectures 46:36
Review of Linear Classifiers 7 lectures 50:14
Linear SVM 10 lectures 01:06:27
Duality 7 lectures 43:47
Kernel Methods 9 lectures 51:14
Implementations and Extensions 8 lectures 54:21
Neural Networks (Beginner’s Corner 2) 8 lectures 50:24
Appendix / FAQ 12 lectures 02:28:26
Calculus, Matrix Arithmetic / Geometry, Basic Probability
Python and Numpy coding
Logistic Regression
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
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