Machine Learning Examples

Explore examples in machine learning solved with Neural Designer, and learn to develop your models.

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Iris flowers classification

Classify among three species of iris
flowers (setosa, versicolor, or virginica).

Airfoil self-noise prediction

Predict the noise an airfoil generates
from his aerodynamic properties.

Breast cancer diagnosis

Diagnose the presence of breast cancer
from digitized images of cell nuclei.

Palmer penguin classification

Classify Palmer Archipelago
(Antarctica) penguins

Concrete properties assessment

Design concretes having some properties
with the highest possible quality.

Fault detection and diagnosis

Predict malfunctions of
a liquid ultrasonic flowmeter.

Employee attrition

Identify which employees are the most
likely to switch to another company.

Banknote authentication

Accurately classify
fraudulent notes.

Bank marketing campaign

Predict whether a client is going
to submit a long-term deposit or not.

Credit risk assessment

Predict customers
default payments in a bank.

Tree wilt detection

Detect diseased trees
through image analysis.

Combined cycle power plant

Predict the electricity generated
by a combined cycle power plant.

Solar power generation

Predict the power generated
by a solar plant.

Blood donation campaign

Create a model that can predict which
people are more likely to donate blood.

Urinary inflammation diagnosis

Diagnose the urinary bladder using
a dataset from a medical expert.

Power plant gas emissions

Model the pollutant emissions
and give a reduction solution.

Leukemia microarray analysis

Diagnose the type of leukemia
using DNA coding.

Nanoparticle adhesive strength

Predict the vascular adhesion of nano
particles from their wall shear rate.

Aquatic toxicity

Model the level of
toxicity of a waterbody.

Activity recognition

Recognize human activities in real life
situations through activity recognition.

Yachts hydrodynamics modeling

Predict the hydrodynamic performance
of yachts from dimensions and velocity.

Wine quality improvement

Model wine quality based on
physicochemical tests.

Telecommunications churn

Prevent customer churn in
telecommunications companies.

Bank churn

Predict the churn of customers
in a bank.

Wind turbines' power curve

Model the theoretical power
curve of a set of wind turbines.

Dermatological diseases

Diagnose dermatological diseases from
clinical and histopathological features.

Obesity level

Estimate obesity levels based on
eating habits and physical condition.

Liver disease diagnosis

Diagnose liver diseases
from different types of analysis.

Target insurance customers

Accurately classify customers that are
interested in a vehicle insurance.

Credit card fraud detection

Detect and prevent credit card
fraud from payment's features.

Diabetic retinopathy prognosis

Prognosticate a future event,
diabetic retinopathy.

Bankruptcy prevention

Prevent bankruptcy based
on business features.

Colon cancer treatment

Colon cancer treatment
using levamisole and fluorocil.

Car CO2 emissions

Estimate CO2 emissions from
cars related to their engines.

Car price assignment

Predict car prices as a
function of certain car features.

Electric motor Digital Twin

Build a Digital Twin of an
electric car motor.

QSAR Biodegradation

Predict biodegradability of
different chemicals.

E-nose for alcohol detection

Use electronic nose to detect
different types of alcohol.

Forest fires

Predict probability of
forest fire risk.

Superconductor critical temperature

Determine the critical temperature
of different chemical compounds.

Orbit type classification

Classify the different
asteroid orbit.

Star type classification

Identify the different
star types.

Gamma Telescope

Analize the gamma-ray
shower type.

Higgs Boson

Detect Higgs Boson

Inflation prediction

Predict future inflation based
on macroeconomic features.

Lung cancer

Early detection of
lung carcinoma.

Colon cancer liver metastasis

Predict liver metastasis in colon
cancer using mutational data.

Breast cancer mortality

Predict breast cancer mortality
from patients gene panel.

Lung cancer recurrence

Predict lung cancer recurrence
from patients gene expression.