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Machine Learning

Machine Learning
Machine Learning is all about software that can “learn” from data. As a machine learning company we can help you reveal hidden patterns and make data-driven forecasts using machine learning services.

Elinext has been intensively working with machine learning solutions for the last 7 years. We already have a scope of successful ML projects in HealthTech, FinTech, media, and other industries.
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Our AI and ML Services
Our Expertise in Machine Learning Software Development
Expertise
Dataset analysis
Image recognition
Text categorization
Text recognition
Media analysis
Dataset analysis
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ML can be applied to any amount of data. Popular data analytics solutions include automatic text analysis and translations, medical diagnostics, stock market analysis, image recognition, product recommendation systems, fraud detection, and many others. ML can model dependencies between variables or reveal tendencies in variables of any scale.

Image recognition
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You can delegate us development of such machine learning solutions as image classification, image localization, object detection, or image segmentation. If you have a dataset with images of objects from different classes, we can train a model which will recognize them too.

Text categorization
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Machine learning model can be trained on a dataset of text pieces marked with categories. For example, text descriptions of products. After training, the system will match texts with their closest category.

Text recognition
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ML can help with the automatic extraction of words and entities from texts. You can have documents in MS Word, pdf, or image formats. ML techniques can process them and find information that is important for you.

Media analysis
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Do people react positively or negatively about your product in their tweets? Can messages be divided into several groups according to their content? Is there a correlation between mentions of different topics in the news?
Using ML, we can help you to reveal trends in news and social media ― build effective sentiment analysis tools.

Our Machine Learning Development Solutions
Solutions
Elinext is ready to develop ML solutions from scratch or you can choose the service you need. Here’s the scope of our available Machine Learning services:
Machine Learning software development
Technical specifications preparation
Consulting
Statistical Analysis
Machine Learning software development
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Development and deployment of ML models is our main service in the frame of ML. Very often a client needs ML solution for their website. Elinext web developers create a website, ML engineers develop models, and we integrate models into the website. All specialists work for your project as one team so you can be sure that there are no contradictions in technologies and there’ll be no need for adjustments later.

Technical specifications preparation
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Clients come to us as a machine learning development company with different levels of knowledge about their products. Our business analysts and ML engineers help to prepare detailed product specifications. Technical requirements for ML models are discussed and prepared with ML engineers who actively participate in product development from the first day until the end of the project. You can be sure that there is no loss of information between specification development and product development phases.

Consulting
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Often, the only thing a client has is a high-level target of their product. We help clients by suggesting a list of product features that we can develop using existing data.

Statistical Analysis
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Our specialists analyze a specific dataset, test hypotheses, and make conclusions using statistical models. We suggest working with Cross-Sectional, Time Series, and Panel Data.

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Industries We Serve with Machine
Learning Software Development

Services
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Healthcare
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Financial & banking
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E-commerce
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Insurance
Healthcare

Elinext has wide expertise in creating machine-learning-based applications and web solutions for healthcare. ML-solutions can be used to predict illnesses and health risks, to model disease progression. They also are widely used by physicians for image analysis, etc.

Financial & banking

Elinext has experience in the development and implementation of analytical tools for financial markets, e.g., application of CAPM, yield curve modeling. We can help you with both the creation of software tools for financial analysts and with market analysis itself (with a combination of financial theory and ML techniques like artificial neural networks).

E-commerce

Elinext can help you to build an e-commerce website using ML technologies. Machine learning applications are widely used in e-commerce for inventory management, recommendation engines, customer offer personalization, manual processes automation, etc.

Insurance

Machine learning can be used by insurance companies for fraud detection, data-driven management, for building recommendation tools and assistants for clients, as well as to set assumptions and automate analytical activities such as risk analyses, pricing models, etc.

What Benefits does ML Bring Business?

Benefits
If you need to process a lot of human-generated texts, you need natural language processing tools. If you need to recognize objects in images or videos, you need computer vision. There is almost no niche where ML couldn’t be helpful. Here are the major benefits of ML:
Data-Driven
Business Decisions
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ML helps businesses make decisions faster and based on real-time automated analysis free of human errors.
Increased Efficiency
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ML can process an enormous amount of data. If your business uses large data volumes, ML will be much more efficient than traditional data analysis.
More Time
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Using ML, you can automate numerous manual operations. ML allows automatically extracting, systematizing, and analyzing data from texts and images.
Reduced Costs
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ML-based algorithms help you to save a lot of money and set complicated tasks for analysis which was practically impossible before the introduction of ML.
Security
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Using ML, you can improve your business’s safety and security. ML algorithms help to check businesses’ cybersecurity and show security weaknesses.

Technology We Use

Technology Stack
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Frameworks and libraries - Tensorflow, SpaCy, Gensim, FastText, Statsmodels, Scikit-learn, OpenCV, Numpy, Pandas, SciPy, transformers, TadGAN
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ML as a microservice - ML solution can be packed into Docker Container with REST API built with Flask or FastAPI frameworks
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Cloud Computing
Platforms -
Amazon Web Services (AWS). Training and deploy of ML models with AWS Sagemaker, features preprocessing and model training with Apache Spark
ML models types:
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Multilayer Perceptron (MLP)
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Recurrent Neural Networks (RNN, LSTM etc.)
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Convolutional Neural Networks (CNN)
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Transformers (BERT etc.)
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Generative Adversarial Networks (GAN)
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Special and composite model architectures (YOLO, Mask R-CNN etc.)
FINANCIAL MODELS:
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Bonds analysis
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Stock markets fundamental analysis
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Portfolio optimization
STATISTICAL MODELS:
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Ordinary Least Squares (OLS)
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Maximum Likelihood (ML)
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Generalized Linear Model (GLM)
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Generalized method of moments (GMM)
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Time series analysis (ARIMA, ARCH/GARCH, threshold models)
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Pooled OLS, fixed and random effects models, first differences
Case studies
Case studies
Elinext has been intensively working with machine learning solutions for the last 3 years. We already have a scope of successful ML projects in HealthTech, FinTech, media, and other industries.
Trained Machine Learning Algorithm Development For Teeth Detection

Elinext developed an ML-based tooth detection tool for a US healthcare company, enabling accurate identification of teeth and dental issues through telemedicine, with potential for further feature expansion.

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Code Optimization for a Biopharmaceutical Company in Germany

A German company that provides software solutions for the biopharma industry in predictive biomanufacturing hired us to optimize the code in several modules and assist with the research and development phase.

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AI-Tool For Monitoring Telecom Networks Worldwide

Elinext developers and QAs have been involved in serious rework and refactoring of UI approaches, implementing integration with about 15 third-party products, adopting serious quality control processes and standards, developing and improving a great number of complicated algorithms and applications.

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Predictive Analytics for Forecasting Demand in Retail

How to create an efficient machine learning solution for retail? Learn in our new case study.

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Hate Speech Detector and FAQ Chatbot

A new eCommerce company hired Elinext to build a smart application that filters out inappropriate reviews and answers website visitors’ questions.

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Pneumonia Diagnosis Tool

A company developing a healthcare platform hired Elinext to help it build a pneumonia diagnosis tool.

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Application for Sentiment Voice Analysis

Elinext teams faced a challenging task to develop an application with voice analysis that would provide a call center with the ability to organize the working process in the most efficient manner, by understanding what their customers and employees really feel and think.

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Social Media Sentiment Analysis Software for an Analytical Agency

Elinext teams faced a challenging task to develop a solution that would allow sentiment analysis in Twitter, providing our client with the ability to receive insightful information on how Twitter users react to certain politicians, their actions, speeches, etc., and then act accordingly.

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