Genetic Algorithm in Machine Learning: Diagram & Feature Selection
Many typical machine learning applications, from customer targeting to medical diagnosis , arise from complex relationships between features...
Read moreData science and machine learning blog
Welcome to the Neural Designer blog! Here you will find posts about artificial intelligence, machine learning and neural networks written by professional data scientists.
Neural Network Training Algorithms: The 5 Main Methods
The training algorithms orchestrates the learning process in a neural network , while the optimization algorithm (or optimizer) fine-tunes...
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Neural Network Model: The Modeling Process in 6 Steps
The modeling process is the sequence of steps used to build a mathematical model that represents a system or phenomenon from data, so it can...
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Mathematics of the perceptron neuron model
One of the hottest topics in artificial intelligence and machine learning is neural networks . These are computational models based on the...
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Model steel properties using machine learning
This example aims to use machine learning to predict steel properties only by knowing the elements' concentration percentage and the...
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Model water toxicity using machine learning
In this example, we build a machine learning model to calculate water toxicity using actual data from a water body. Many chemicals partition...
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Improve the performance of a power plant using machine learning
This example uses machine learning to model the energy generated as a function of exhaust vacuum and ambient variables and use that model to...
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Detect forged banknotes using machine learning
This example builds a machine learning model to detect forged banknotes accurately. For that, we use a set of images taken from genuine and...
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Predict airfoil self-noise using machine learning
In this example, we use machine learning to predict airfoil self-noise using data from a series of aerodynamic and acoustic tests. The noise...
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Reduce emissions from a power plant with machine learning
A combined-cycle power plant comprises gas turbines, steam turbines, and heat recovery steam generators. In this type of plant, the...
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Neural Designer technical features
Neural Designer implements the most innovative artificial intelligence techniques. Some of the main algorithms it contains are listed below....
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Neural Designer's unique features
Neural Designer implements the most innovative machine learning algorithms in the marketplace. In this post, we describe some of the features...
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Machine learning examples in finance
Artificial intelligence can be used to automate trading activities and provide decision support to investors. As a result, machine learning...
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6 machine learning examples in engineering and industry
Explore machine learning examples to solve a whole range of until now intractable problems in the industry sector. Here you can find several...
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What is Neural Designer?
Neural Designer is a high-performance data-science platform that uses neural networks to help organizations extract insights, predict...
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Neural Designer components
Neural Designer comprises a window to edit your settings, an artificial intelligence engine to perform neural network computation, and...
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Machine learning tutorial: Model selection
Model selection searches for the neural network architecture with the best generalization properties. That is, the process that minimizes the...
Read moreMachine learning tutorial: Model deployment
Deployment in machine learning is the process of applying a model to make predictions on new data. It involves organizing and presenting the...
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Machine learning tutorial: Data set
This tutorial explains the role of the dataset in building machine learning models. A dataset is a table of rows and columns that provides...
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Machine learning in energy and utilities: 5 practical examples
Artificial intelligence is changing how industries create and deliver products and services. Here, you can find some worked examples of the...
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7 machine learning examples in environment
Artificial intelligence helps us to fight against climate change and to preserve the environment in several ways. Here you can find some...
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Machine learning: Training strategy - tutorial
The machine learning training strategy is the method that drives the learning process of a neural network. It searches for the parameter...
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Machine learning tutorial: Testing analysis
The purpose of testing in machine learning is to compare the outputs from the neural network against targets in an independent set (the...
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Use Neural Designer without an Internet connection
Neural Designer is a powerful tool for designing and training neural networks, but what if you need to use it in an offline environment? In...
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Mathematics of artificial intelligence: the learning problem in neural networks
The mathematics behind Artificial Intelligence can be challenging to understand. It is essential to comprehend them to apply machine learning...
Read moreMachine learning tutorial: Model types
This tutorial describes different machine learning model types. Neural networks use information in the form of data to generate knowledge in...
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Machine learning tutorial: Neural networks
In machine learning, neural networks are biologically inspired computational models composed of interconnected artificial neurons. In...
Read moreBuild a neural network in 7 steps
In this tutorial, you will build a neural network that approximates a function defined by a set of data points. Download the data for this...
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Neural Networks Tutorial: Architecture & Learning
Index: 1. Model types 2. Data set 3. Neural network 4. Training strategy 5. Model selection 6. Testing analysis 7. Model deployment In this...
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What is advanced analytics?
Advanced analytics refers to a set of methods that go beyond traditional reporting to extract deeper insights from data. Organizations are...
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Types and uses of variables in machine learning
In machine learning, a variable refers to a feature or attribute used as input for training and making predictions. In this context, we...
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Use Neural Designer in the cloud with Amazon Web Services (AWS)
This User's Guide aims to help you use Neural Designer in the cloud with the Amazon Web Services marketplace. Keep in mind that you will need...
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How is a dataset for machine learning?
A machine learning dataset collects data to create and train an approximation, classification, or forecasting model. Central to this process...
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Colon cancer metastasis risk prediction simulator
Early detection and prognosis of colon cancer metastasis are critical for patient survival, yet remain challenging due to the interaction of...
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Handle missing values in machine learning
In this post, we explain the primary methods for handling missing values in machine learning and when to use each one. A common challenge...
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Training, validation and testing samples in machine learning
Introduction In machine learning, samples represent all variables in the dataset and are divided into training, validation, and test samples....
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3 methods to treat outliers in machine learning
This post examines three key methods for handling outliers in machine learning. Outliers are data points that are distant from the rest. They...
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The Rosenbrock benchmark suite for machine learning
There are numerous repositories with a large number of datasets for machine learning. Some of the most important ones are the UCI Machine...
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Machine learning examples in physics: 5 case studies
Machine learning has brought about one of the biggest revolutions in physics. In this article, we present several machine learning examples...
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Use Neural Designer models in Microsoft Power BI
Although deploying a model once trained is essential to benefit from working with Machine Learning, it can also be one of the hardest tasks...
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Export Neural Designer models to Python
Neural Designer is a powerful tool for building and analyzing neural network models. However, when working with these models, it is crucial...
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Target blood donors using machine learning
Introduction Machine learning models for blood donation prediction can help healthcare organizations improve donor recruitment and optimize...
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Diabetic retinopathy risk prediction using machine learning models
Introduction Machine learning for diabetic retinopathy risk prediction aids early detection, enabling timely interventions and reducing...
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Metastasis prediction using machine learning
Introduction Colorectal cancer frequently leads to liver metastasis, which significantly worsens patient prognosis. Therefore, early...
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Human activity recognition machine learning with smartphone data
Introduction Human activity recognition (HAR) using machine learning can support healthcare applications by analyzing smartphone movement...
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Obesity risk prediction using machine learning models
Introduction Obesity prediction with machine learning supports healthcare professionals in delivering personalized recommendations and...
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Model nanoparticle adhesive strength using machine learning
Introduction Nanoparticle-based machine learning can predict their vascular behavior, particularly adhesion to vessel walls, which is crucial...
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16 machine learning examples in healthcare and medicine
The power of artificial intelligence for analyzing health data will empower physicians and speed up decision-making at clinics and hospitals....
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Breast cancer mortality prediction with machine learning
Introduction Machine learning can help predict 5-year mortality risk in breast cancer, a heterogeneous disease influenced by clinical...
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Machine learning leukemia diagnosis from microarray data
Introduction Accurate differentiation between acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) is critical, since...
Read moreDiagnose dermatological diseases using machine learning
Introduction Machine learning is enhancing dermatological diagnosis by improving accuracy in identifying erythemato-squamous diseases (ESDs),...
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Pancreatic cancer prediction with machine learning
Introduction Machine learning is helping improve early detection of pancreatic ductal adenocarcinoma (PDAC), a cancer with low survival rates...
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Patient screening for lung cancer using machine learning
Introduction Lung cancer is the leading cause of cancer-related deaths worldwide, and early detection is critical since symptoms often appear...
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Detect gamma rays using machine learning
The objective is to design a machine learning model that accurately detects gamma rays and distinguishes them from the background. The...
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Cervical cancer prognosis using machine learning
Early detection of cervical cancer is crucial for increasing survival rates, minimizing treatment intensity, and reducing mortality and...
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Diagnose liver diseases using machine learning
Introduction Machine learning has improved early detection and clinical decision-making in liver disease. Conditions such as Hepatitis C,...
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Machine learning for treatment prescription of colon cancer
Introduction Colon cancer is a leading cause of cancer-related deaths, and treatment outcomes depend on clinical and demographic factors....
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6 testing methods for binary classification models
Introduction Evaluating a machine learning model is essential to ensure it generalizes well—that is, it performs reliably on unseen data....
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Breast Cancer Diagnosis Machine Learning
Introduction Breast cancer is one of the most common malignancies, and early detection is essential to improve outcomes. Fine needle...
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Diagnosis of urinary diseases using Machine Learning
Introduction This application uses machine learning to assist health professionals in identifying renal pelvis nephritis, providing a...
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Develop an e-nose to detect alcohols using machine learning
This example builds a machine learning model to develop an e-nose to detect alcohols. Scientists design electronic noses to mimic humans'...
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Feature selection algorithms in machine learning
Feature selection algorithms help you choose the most relevant variables for building machine learning models. They are crucial in...
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Applications of machine learning in the pharmaceutical industry
In the pharmaceutical and clinical diagnostics industries, machine learning is transforming product development by accelerating innovation,...
Read moreIntegrate Neural Designer in your application
Integrating Neural Designer into your application can simplify the adoption of machine learning within your business. Companies often find it...
Read moreAssess the risk of company bankruptcy through machine learning
This example aims to build a machine learning model to assess bankruptcy risk based on qualitative parameters provided by experts. In...
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Target customers for a banking product using machine learning
This example aims to target customers and predict whether bank clients will subscribe to a long-term deposit using machine learning. Customer...
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Reduce customer churn in a bank using machine learning
This example uses customer data from a bank to build a predictive model for identifying clients who are likely to churn. More specifically,...
Read moreLearning center
Welcome to the Neural Designer learning center! Here, you will find a variety of online courses to help you start with machine learning and...
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Detect the Higgs boson using machine learning
In the early 1960s, particle physicists needed a theory to explain the origin of mass in the universe. In 1964, Peter Higgs theorized the...
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Predict forest fires using machine learning
In this post, we develop a machine learning model to predict forest fires. Forest fires lead to deforestation, biodiversity loss, air...
Read moreMachine learning examples
Explore examples in machine learning solved with Neural Designer and learn to develop your models. Download Neural Designer to follow these...
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5 machine learning examples in retail
Customer targeting, churn prevention, or sales forecasting are some examples in retail where machine learning is achieving great results....
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5 machine learning examples in physics
Machine learning has brought about one of the biggest revolutions in physics. Here, you can explore several examples of applying machine...
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5 machine learning examples in chemistry
Artificial intelligence and machine learning are transforming chemistry by enabling faster discoveries, accurate predictions, and optimized...
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6 machine learning examples in banking & insurance
Artificial intelligence has brought upon one of the biggest revolutions in the banking & insurance sectors.Here you can explore several...
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4 machine learning examples in the automotive industry
In this section, we’ll explore some real-world machine learning examples in the automotive industry that are being used. These examples,...
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Prevent employee attrition using machine learning
In this example, we build a machine learning model to predict employee churn and help companies reduce staff turnover. Employee attrition is...
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Build a digital twin of an electric motor using machine learning
This example shows how machine learning can create a digital twin of an electric motor. With the rise of electric vehicles, companies need...
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Assess the risk of default payments using machine learning
The objective of this example is to predict the default risk of a bank's customers using machine learning. The primary outcome of this...
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Detect fraud in credit card transactions using machine learning
In this example, we develop a machine learning model to detect fraudulent credit card transactions. Credit card fraud occurs when someone...
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Model concrete properties using machine learning
This example aims to build a machine learning model to design concrete mixtures with specified properties and reduced costs. To do that, we...
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Pricing cars using machine learning
A Chinese automobile company aspires to enter the US market by setting up its manufacturing unit and producing cars locally to compete with...
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Estimate car emissions using machine learning
In this example, we will build a machine learning model to estimate car emissions, a topical issue that should raise awareness in the reader....
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Breast cancer mortality prediction machine learning simulator
We have created a machine learning model to evaluate the mortality in breast cancer patients. This model uses clinical, expression, and...
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Neural networks selected bibliography
Fundamentals of recurrent neural network (RNN) and long-short term memory (LSTM) network. A Sherstinsky. Physica D: Nonlinear Phenomena, 404,...
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Yacht hydrodynamics modeling using machine learning
In this example, we build a machine learning model to predict the hydrodynamics performance of sailing yachts as a function of hull geometry...
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Improve wine quality using machine learning
This example demonstrates how machine learning can predict wine preferences to support oenologists in enhancing wine quality. The model...
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Model the power curve of a turbine with machine learning
Using actual data from a wind turbine field and a neural network, we will develop a machine learning model that can predict the theoretical...
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Target customers for a vehicle insurance using machine learning
An insurance company that already offers health insurance now wants to target customers likely to be interested in vehicle insurance. To do...
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Detect tree wilt with machine learning
This example uses machine learning to develop a classification method to detect tree wilt (Japanese oak wilt and Japanese pine wilt). For...
Read moreReduce customer churn in a telco using machine learning
Customer churn is a big problem for telecommunications companies. Indeed, their annual churn rates are usually higher than 10%. Therefore,...
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Model superconductors' critical temperature using machine learning
For this study, we use machine learning to model superconductors' critical temperature from an extensive data set of the chemical properties...
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Star types classification using machine learning
The main goal is to design a classification machine learning model that classifies different star types. The categories are Red Dwarf, Brown...
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Predict the generation of a solar plant using machine learning
In this example, we develop a machine learning model to predict power generation at a solar plant located in Berkeley, CA. We utilize various...
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Predict chemical biodegradability with machine learning
This example aims to catalog different chemical biodegradability using machine learning. QSAR (Quantitative Structure-Activity Relationships)...
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Predictive maintenance using machine learning
In this example, we build a machine learning model used as predictive maintenance to detect faults in an ultrasonic flow meter. Predictive...
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Classify Palmer penguins using machine learning
This example builds a machine learning model to classify size measurements for adult foraging penguins near Palmer Station, Antarctica. We...
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Classify asteroid orbits using machine learning
The primary objective is to develop a machine learning model for classifying asteroid orbits. This example is solved with the data science...
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Predict a country's inflation through machine learning
This example aims to predict inflation from the macroeconomic data of a country using machine learning. Inflation is the rate of increase in...
Read moreUser's guide
This user's guide aims to help you get the most out of Neural Designer . Technical Features This article presents and explains the lists of...
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Inspect milk quality using machine learning
In this example, we will build a machine learning model to inspect milk quality by seven observable milk variables. Milk can be classified in...
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Market basket analysis using machine learning
Market basket analysis is a well-known problem in data mining that can help businesses better understand customer behavior and optimize their...
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The 3 main types of machine learning models
Models describe a real-world system or process using mathematical concepts. They are used to make decisions or predictions in various fields...
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5 applications of learning analytics
Every day, a vast amount of data is generated by people and companies. This data generation has been growing exponentially in the last few...
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Can we predict a pathway status using gene expression?
Abnormal pathway activation may lead to diseases. In this context, if we assume that a mutation in a core gene leads to that status, can we...
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Insurance risk prediction with machine learning
Insurance risk prediction with machine learning is essentially a modeling task: estimate mortality from demographic, medical, and behavioral...
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How to benchmark the performance of machine learning platforms
This post aims to identify the most critical key performance indicators (KPIs) and define a consistent measurement process. In machine...
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Assess death risk after heart failure using machine learning
This example assesses the death risk of patients who experienced heart failure. Cardiovascular diseases are the leading cause of death...
Read moreExport Neural Designer models to JavaScript
Contents Introduction . How to export the mathematical expression? Using a Pre-Trained Neural Network Model in JS Conclusions Tutorial video...
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Energy consumption of TensorFlow and Neural Designer
TensorFlow and Neural Designer are popular machine learning platforms developed by Google and Artelnics , respectively. Although all those...
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Forecast electricity demand using machine learning
Forecasting power demand is crucial for planning and operating electrical systems. Utilities use short-, medium-, and long-term forecasting,...
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How to check if the data distribution is correct in machine learning
In machine learning, plotting the distribution of variables in a dataset is a visual aid for studying their distribution. Sometimes, the...
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Customer targeting using machine learning
Customer targeting is the process of analyzing customer features (such as age, education, interests, and spending habits) to select those...
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Prevent urban crime using machine learning
The volume, variety, and velocity of information stored in security and crime prevention institutions have increased significantly. The...
Read moreMetastasis risk assessment using machine learning
Advancements in the field of medicine have paved the way for innovative approaches to cancer care, and one such groundbreaking avenue is the...
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Data capacity of TensorFlow, PyTorch, and Neural Designer
--> In this post, we compare the load capacity of three machine learning platforms: TensorFlow , PyTorch and Neural Designer for an...
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9 applications of machine learning in cancer
The ability of Machine Learning tools to detect critical features from complex datasets reveals their importance in cancer diagnosis. The...
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Auto-associative neural networks (AANNs) for predictive maintenance
1. Introduction Predictive maintenance uses data analysis and machine learning techniques to identify potential equipment failures before...
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Air compressor predictive maintenance using machine learning
In this article, we develop a predictive maintenance model for air compressors to improve performance and reliability. Air compressors are...
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Forecast oil production using machine learning
In this example, we build a machine learning model to forecast the oil production from the field for the following days or weeks. For that,...
Read more6 business intelligence applications: use cases & benefits of predictive analytics
Predictive analytics extracts information from data sets to discover relationships, recognize patterns, forecast trends, find associations,...
Read moreWhat is machine learning?
Machine learning is present all around us. For example, when you use voice recognition or get product recommendations on your phone, you are...
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Training speed of TensorFlow, PyTorch, and Neural Designer
This post compares the GPU training speed of TensorFlow, PyTorch and Neural Designer for an approximation benchmark. TensorFlow , PyTorch and...
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Understanding text classification with machine learning
Text classification is a machine learning technique that assigns predefined categories to free-form text. With text classifiers, you can...
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Useful statistics of a dataset in machine learning
When building a machine learning model, it’s essential to understand the ranges of all variables, as data statistics provide insight into the...
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Predict failure of space flights using machine learning
In this example, we build a machine learning model to predict whether a space flight succeeds or fails based on variables related to the...
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Forecast sales of a retail store using machine learning
Sales forecasting is a crucial task for managing a store, and machine learning can help identify the factors that influence sales in a retail...
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Classify raisins using machine learning
This study aims to classify different raisins using machine learning. Several traditional methods exist for assessing and determining the...
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Understanding principal components analysis (PCA)
Principal components analysis (PCA) is a statistical technique that allows identifying underlying linear patterns in a data set so it can be...
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Precision of TensorFlow, PyTorch, and Neural Designer
This post compares the training precision of TensorFlow, PyTorch, and Neural Designer for an approximation benchmark. TensorFlow , PyTorch...
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Model the radiation efficiency of antennas using machine learning
This example builds a machine learning model to evaluate the radiation efficiency of patch antennas with different features. We used data...
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Assess a chemical's partition coefficient using machine learning
In this example, we will build a machine learning model to assess the n-octanol-water partition coefficient. The n-octanol-water partition...
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Neural Designer in scientific research
The scientific and research community has used Neural Designer widely. Many articles use this program to support or even fully develop their...
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Classify iris flowers using machine learning
Classification of iris flowers is perhaps the best-known example of machine learning. The aim is to classify iris flowers among three species...
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Forecasting model of air pollution in Madrid
This is the model we obtained in the example of forecasting the levels of air pollution for Madrid. PM2.5 PM10 O3 NO2 SO2 PM2.5 refers to...
Read moreForecast air pollution in a city using machine learning
Air pollution is one of the significant problems the world faces. Having a way to monitor these levels, allowing for informed decisions, can...
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Detect anomalies in beach water quality using machine learning
A historical example of detecting unusual beach water quality samples with an auto-associative network. Current Neural Designer calls this model Anomaly Detection.
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