Home AI Courses ML in Mathematics: Multivariate Calculus

ML in Mathematics: Multivariate Calculus

(0 reviews)

This course offers a concise summary of essential multivariate calculus for machine learning, including practical tools, vector calculations, function approximation, and neural network applications, to build confidence for advanced studies.

Key AI Functions:

Linear Regression,Vector Calculus,Multivariable,Calculus Gradient,Descent

Description

Reviews

Alternative Tools

Description for ML in Mathematics: Multivariate Calculus

This course provides a succinct summary of the multivariate calculus necessary for the development of common machine learning techniques, ranging from fundamental slope concepts to formal gradient definitions.

Create a collection of calculus instruments, acquire the ability to calculate vectors on multidimensional surfaces, and apply this knowledge through interactive activities.

Investigate the application of calculus to approximate functions and evaluate the precision of these approximations, as well as its role in neural network training.

Acquire a thorough comprehension of calculus and the requisite language to conduct independent research, thereby fostering confidence for more advanced machine learning courses.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by Imperial College London

Duration: 17 hours (approximately)

Schedule: Flexible

Reviews for ML in Mathematics: Multivariate Calculus

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

Planning Gen AI Project

Gen AI Empowering Executives & Business Leaders

IBM AI Product Manager

Gen AI Assisting Data Analysts

Gen AI Assistants

Alternative Tools for ML in Mathematics: Multivariate Calculus

Supervised ML: Regression and Classification

Learn to build and train supervised machine learning models for binary classification and prediction tasks using Python with NumPy and scikit-learn libraries.

#Linear Regression #Regularization to Avoid Overfitting

CertNexus Certified AI Practitioner Professional Certificate

Become an expert in the field of artificial intelligence. Develop effective strategies for the application of Artificial Intelligence techniques to address business challenges.

#Linear Regression #Machine Learning (ML) Algorithms

Supervised ML: Regression

Besides Python programming and data science fundamentals, the course covers supervised machine learning regression, which includes training models for continuous outcomes, error metrics, Elastic Net, LASSO, Ridge regularization, and data science fundamentals for aspiring data scientists.

#Linear Regression #Machine Learning (ML) Algorithms

ML Regression

Master regression by predicting house prices, investigate regularized linear regression, manage extensive feature sets, and employ optimization algorithms to make precise predictions with large datasets.

#Linear Regression #Ridge Regression