Machine Learning - STANFORD SCHOOL OF ENGINEERING offered by Stanford University
- Private University
8180 acre campus- Estd. 1885
Machine Learning - STANFORD SCHOOL OF ENGINEERING at Stanford University Overview
Machine Learning - STANFORD SCHOOL OF ENGINEERING
at Stanford University
Duration | 10 weeks |
Total fee | ₹3.68 Lakh |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Course Level | UG Certificate |
Machine Learning - STANFORD SCHOOL OF ENGINEERING at Stanford University Highlights
Machine Learning - STANFORD SCHOOL OF ENGINEERING
at Stanford University
- Broad introduction to machine learning and statistical pattern recognition
- Key topics covered: Basics concepts of machine learning, Evaluating and debugging learning algorithms and more
- Learn from expert instructors of Standford University
Machine Learning - STANFORD SCHOOL OF ENGINEERING at Stanford University Course details
Machine Learning - STANFORD SCHOOL OF ENGINEERING
at Stanford University
Skills you will learn
Who should do this course?
- Prerequisites - Linear algebra, basic probability and statistics.
What are the course deliverables?
- Basics concepts of machine learning
- Generative learning algorithms
- Evaluating and debugging learning algorithms
- Bias/variance tradeoff and VC dimension
- Value and policy iteration
- Q-learning and value function approximation
More about this course
- "Artificial Intelligence is the new electricity." -Andrew Ng, Stanford Adjunct Professor
- Computers are becoming smarter, as artificial intelligence and machine learning, a subset of AI, make tremendous strides in simulating human thinking. Creating computer systems that automatically improve with experience has many applications including robotic control, data mining, autonomous navigation, and bioinformatics.
- This course provides a broad introduction to machine learning and statistical pattern recognition. Learn about both supervised and unsupervised learning as well as learning theory, reinforcement learning and control. Explore recent applications of machine learning and design and develop algorithms for machines.
Machine Learning - STANFORD SCHOOL OF ENGINEERING at Stanford University Curriculum
Machine Learning - STANFORD SCHOOL OF ENGINEERING
at Stanford University
Basics concepts of machine learning
Generative learning algorithms
Evaluating and debugging learning algorithms
Bias/variance tradeoff and VC dimension
Value and policy iteration
Q-learning and value function approximation
Other courses offered by Stanford University
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Machine Learning - STANFORD SCHOOL OF ENGINEERING at Stanford University Contact Information
Machine Learning - STANFORD SCHOOL OF ENGINEERING
at Stanford University