Predictive Modeling and Machine Learning with MATLAB
Key Takeaways
Builds a predictive model using MATLAB for machine learning tasks
Original Description
In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do.
These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed courses 1 through 2 of this specialization.
By the end of this course, you will use MATLAB to identify the best machine learning model for obtaining answers from your data. You will prepare your data, train a predictive model, evaluate and improve your model, and understand how to get the most out of your models.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Pipelines
View skill →Related Reads
📰
📰
📰
📰
The Mental Model of PyTorch: Build a Neural Network in 5 Phases
Medium · Deep Learning
Automatic Relevance Determination Regression for Time Series Forecasting
Medium · Data Science
Deploying Multi-Turn RL Infrastructure for Amazon Nova on Amazon SageMaker HyperPod
AWS Machine Learning
Python for Data Science — Sampling and Why Your Conclusions Can Be Wrong
Medium · Machine Learning
🎓
Tutor Explanation
DeepCamp AI