AI and Statistics

Data preparation, design, simulation, and deployment for machine learning and deep neural networks

MATLAB^® makes data science easy with tools to access and preprocess data, build machine learning and predictive models, and deploy models.

Using apps or with just a few lines of MATLAB code, you can apply statistical, machine, and deep learning techniques to your work for designing algorithms, preparing and labeling data, or generating code and deploying to embedded systems. Extend AI modeling and data fitting workflows with specialized tools for:

Data types such as images, video, signals, audio, and text
Applications such as computer vision, audio and signal processing, text analytics, wireless communications, and automated driving

Workflow for AI from data preparation to modeling to system design and deployment

Products for AI and Statistics

Deep Learning Toolbox

Design, train, analyze, and simulate deep learning networks

Statistics and Machine Learning Toolbox

Analyze and model data using statistics and machine learning

Curve Fitting Toolbox

Fit curves and surfaces to data using regression, interpolation, and smoothing

Text Analytics Toolbox

Analyze and model text data

Topics

AI Basics

Machine Learning in MATLAB (Statistics and Machine Learning Toolbox)
Discover machine learning capabilities in MATLAB for classification, regression, clustering, and deep learning, including apps for automated model training and code generation.
Deep Learning in MATLAB (Deep Learning Toolbox)
Discover deep learning capabilities in MATLAB using convolutional neural networks for classification and regression, including pretrained networks and transfer learning, and training on GPUs, CPUs, clusters, and clouds.
What Is Reinforcement Learning? (Reinforcement Learning Toolbox)
Reinforcement learning is a goal-directed computational approach where a computer learns to perform a task by interacting with an uncertain dynamic environment.

AI Modeling

Train Classification Models in Classification Learner App (Statistics and Machine Learning Toolbox)
Workflow for training, comparing and improving classification models, including automated, manual, and parallel training.
Train Regression Models in Regression Learner App (Statistics and Machine Learning Toolbox)
Workflow for training, comparing and improving regression models, including automated, manual, and parallel training.
Build Networks with Deep Network Designer (Deep Learning Toolbox)
Interactively build and edit deep learning networks in Deep Network Designer.

Simulation and Deployment

Battery State of Charge Estimation in Simulink Using Feedforward Neural Network (Deep Learning Toolbox)
This example shows how to use a feedforward deep learning network inside a Simulink® model to predict the state of charge (SOC) of a battery.
Code Generation for Deep Learning Networks (GPU Coder)
Get started with CUDA^® code generation for image classification networks such as ResNet.
Code Generation for Deep Learning Simulink Model That Performs Lane and Vehicle Detection (Embedded Coder)
This example shows how to generate C++ code from a Simulink® model that performs lane and vehicle detection using convolutional neural networks (CNN).

Related Information

Featured Examples

Time Series Prediction in Simulink Using Deep Learning Network

Use an LSTM deep learning network inside a Simulink® model to predict the remaining useful life (RUL) of an engine. You include the network inside the Simulink model by using a Stateful Predict block, which predicts the RUL at every simulation step.

(Deep Learning Toolbox)

Waveform Segmentation Using Deep Learning

Segment human electrocardiogram signals using time-frequency analysis and deep learning.

(Deep Learning Toolbox)

Train Speech Command Recognition Model Using Deep Learning

Train a deep learning model that detects the presence of speech commands in audio. The example uses the Speech Commands Dataset [1] to train a convolutional neural network to recognize a set of commands.

(Deep Learning Toolbox)

Semantic Segmentation Using Deep Learning

Segment an image using a semantic segmentation network.

(Deep Learning Toolbox)

Increase Image Resolution Using Deep Learning

Create a high-resolution image from a low-resolution image using a very-deep super-resolution (VDSR) neural network.

(Deep Learning Toolbox)

Train Biped Robot to Walk Using Reinforcement Learning Agents

Train a reinforcement learning agent to control a biped walking robot modeled in Simscape™ Multibody™.

(Deep Learning Toolbox)