MATLAB makes data science easy with tools to access and preprocess data, build machine learning and predictive models, and deploy models to enterprise IT systems.
Topics for Data Science
Machine learning is computer modelling of systems making estimations based on deductions by processing mathematical and statistical actions.
Deep learning is a method of machine learning. It allows us to train artificial intelligence to estimate the outputs based on a given data cluster.
Exploratory Data Analysis
Spend less time preprocessing data. From time-series sensor data to images to text, MATLAB datatypes significantly reduce the time required to preprocess data. High-level functions make it easy to synchronize disparate time series, replace outliers with interpolated values, filter noisy signals, split raw text into words, and much more. Quickly visualize your data to understand trends and identify data quality issues with plots and the Live Editor.
Applied Machine Learning
Find the best machine learning models. Whether you’re a beginner looking for some help getting started with machine learning, or an expert looking to quickly assess many different types of models, apps for classification and regression provide quick results. Choose from a wide variety of the most popular classification and regression algorithms, compare models based on standard metrics, and export promising models for further analysis and integration. If writing code is more your style, you can use hyperparameter optimization built into model training functions, so you can quickly find the best parameters to tune your model.
Deploy machine learning models anywhere including C/C++ code, CUDA code, enterprise IT systems, or the cloud. When performance matters, you can generate standalone C code from your MATLAB code to create deployable models with high-performance prediction speed and small memory footprint. You can also export machine learning models for use in Simulink or deploy models to MATLAB Production Server for integration with web, database, and enterprise applications.