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.
Description for ML Regression
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by University of Washington
Duration: 22 hours (approximately)
Schedule: Flexible
Pricing for ML Regression
Use Cases for ML Regression
FAQs for ML Regression
Reviews for ML Regression
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML Regression
Develop and evaluate machine learning models using regression, trees, and unsupervised techniques to address various business challenges.
Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.
Specialization in Machine Learning at BreakIntoAI. Master the fundamental AI concepts and cultivate practical machine learning skills in the beginner-friendly, three-course program by AI visionary Andrew Ng.
Set up for a profession in machine learning. To become job-ready in less than three months, acquire the skills and practical experience that are in high demand.
Master the AI and machine learning toolkit. Mathematics for Machine Learning and Data Science is a Specialization that is accessible to beginners. In this program, you will acquire the basic mathematics tools of machine learning, including calculus, linear algebra, statistics, and probability.
Learn to build and train supervised machine learning models for binary classification and prediction tasks using Python with NumPy and scikit-learn libraries.
Learn fundamental machine learning principles, including K nearest neighbor, linear regression, and model analysis, with prerequisites of Python programming and basic mathematics.
Learn regression analysis, build prediction functions, and develop public data products.
Gain practical experience in implementing Linear Regression with Numpy and Python, understand its significance in Deep Learning, require prior theoretical knowledge of gradient descent and linear regression, and catered primarily to students in the North American region with future plans for global accessibility.
Become an expert in the field of artificial intelligence. Develop effective strategies for the application of Artificial Intelligence techniques to address business challenges.
Featured Tools
Explore the use of generative AI for creating and optimizing code, employing tools like IBM Watsonx Code Assistant and GitHub CoPilot, while addressing associated ethical considerations and challenges.
Learn Python, analyze and visualize data, and apply your skills to data science and machine learning with a practical assignment to acquire hands-on skills for a career in data science.
Effectively employ Azure ML Studio for predictive model development, experiment establishment, and operationalizing machine learning workflows through drag-and-drop modules.
Comprehend generative AI basics, practical applications, ethical implications, and potential impacts on student learning in education.
Learn to import, manipulate, and format data in pandas, optimize parameters, and build, evaluate, and interpret support vector machines.
Compare & Review AI Tool Directory AI Course Marketplace
Today's Featured Blogs
AI and the Future of VotingAI in CookingAI in Enhancing Mindfulness and Meditation How AI is Personalizing Fitness Plans Power of AI in Emotion Recognition AI and Personal Safety
Aimed Labs