Grades:
Median GPA:
Mean GPA:
Click a checkbox to add something to compare.
Search Results
Name | Grades | Rating |
---|---|---|
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ |
Grades:
Median GPA:
Mean GPA:
Click a checkbox to add something to compare.
Search Results
Name | Grades | Rating |
---|---|---|
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ |
Search Results
Name | Grades | Rating |
---|---|---|
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ |
Search Results
Name | Grades | Rating |
---|---|---|
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ | ||
A+ |
Modern Machine Learning Methods
OPRE 7343
Naveen Jindal School of Management
The increasing availability of data provides firms substantial opportunities to leverage modern machine learning methods to inform decision making. This course provides a rigorous introduction to the most commonly used machine learning methods. Emphasis will be on understanding the mathematical and technical aspects behind the algorithms, but students will also implement some of the algorithms (in a programming language of their choice) to gain hands-on experience in applying the learnt methods on real datasets. Topics include classification and regression, clustering, ensemble learning, dimensionality reduction, and deep learning. Instructor consent required. 3 credit hours.
Offering Frequency: Each year
Grades: 38
Median GPA: A-
Mean GPA: 3.586
Click a checkbox to add something to compare.
Modern Machine Learning Methods
OPRE 7343
Naveen Jindal School of Management
The increasing availability of data provides firms substantial opportunities to leverage modern machine learning methods to inform decision making. This course provides a rigorous introduction to the most commonly used machine learning methods. Emphasis will be on understanding the mathematical and technical aspects behind the algorithms, but students will also implement some of the algorithms (in a programming language of their choice) to gain hands-on experience in applying the learnt methods on real datasets. Topics include classification and regression, clustering, ensemble learning, dimensionality reduction, and deep learning. Instructor consent required. 3 credit hours.
Offering Frequency: Each year
Grades: 38
Median GPA: A-
Mean GPA: 3.586
Click a checkbox to add something to compare.