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Machine Learning Development Services

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Experience the potential of custom artificial intelligence and machine learning solutions by Devox. Harness predictive analytics to make informed decisions, automate routine tasks to save time and resources, and personalize customer experiences to stand out in your industry.

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What is Machine Learning

What is Machine Learning and How Can it Help My Business?

Machine Learning (ML) is a branch of artificial intelligence that develops algorithms and statistical models enabling computers to learn and make decisions without being explicitly programmed for specific tasks. Basically, the principle lies in teaching a computer to learn from experience. This technology relies on patterns and inference to perform various functions.

Machine learning solutions development is applicable to various industries, contributing different benefits to everyday operations. For example, it works with data, providing data engineering solutions and predictive analytics, which allows businesses to get better, more comprehensive insights from their work. It’s also powerful in security measures, as it both detects threat, identifies potential risks, and serves as a component of many security solutions like voice or face recognition systems.

Services We Provide

Machine Learning Services We Provide

The notion of a machine learning solution entails a wide range of applications: we can develop a system that will improve your business objectives by many indicators, help your security system, or provide advanced analytics. See what Devox can offer.

  • Consulting and Strategy Development

    Let us provide expert advice on how to leverage ML to meet your business objectives where AI capabilities can be most relevant. Based on your idea, we can tell you whether machine learning solutions are relevant and include strategy development for ML implementation and scaling.

  • Data Processing and Analysis

    Preparing and processing large datasets to be used in machine learning. We create python machine learning solutions like predictive analytics tools: the scope here includes data cleaning, normalization, and transformation to ensure high-quality inputs for the ML models.

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  • Algorithm Selection and Optimization

    Choosing and fine-tuning the most appropriate ML algorithms for the business’s specific challenges and goals. We are testing different models to find the best fit, then adjusting hyperparameters and modifying algorithms to suit the unique characteristics of your data and business objectives.

  • Integration Services

    Integrating ML models into existing business systems and workflows. Our team ensures that the ML solutions work seamlessly with current business processes and software.

  • Training and Testing

    Training ML models with datasets and continuously testing and validating them to ensure accuracy and reliability. We can train and test your existing ML model from scratch; otherwise, this stage is a part of our standard AI development SDLC.

  • Computer Vision

    Training computers to interpret and understand the visual world. Let your system identify, classify and react to objects with precision using digital images from cameras, videos and deep learning models.

  • Voice Recognition

    Devox can create advanced voice-driven applications that understand and respond to human speech. Our services range from voice-activated assistants and customer service bots to speech-to-text solutions and interactive voice response systems.

  • NLP/NLG Development

    Creating intelligent chatbots and virtual assistants that can understand and respond to user queries in natural language. These are tailored for customer support, e-commerce, and interactive user engagement, providing a seamless conversational experience. Alternatively, we can develop an advanced NLP service generating human-like text from structured data for automated report generation, content creation, and providing narrative insights from data analytics.

  • Cloud and On-Premises ML Deployment

    Benefit from flexible deployment options Devox offers, both on cloud platforms for scalability and cost-effectiveness or on-premises for more diligent data security and control. They handle the setup, maintenance, and scaling of the ML infrastructure as per the business needs.

  • ML for IoT (Internet of Things)

    Integrating Machine Learning with Internet of Things (IoT) devices, the company develops smart, connected solutions that can learn and adapt over time. Ideal for businesses looking to enhance their IoT applications with advanced data analysis and predictive capabilities.

Development Process

Our Machine Learning Development Process

While the process of machine learning solutions development is different from classic software development life cycle, we adhere to the latest if we develop a user application for you. In the meantime, see how we develop the AI solution.

01.

01. Problem Definition

We’re starting with gathering your requirements and identifying your business pains, which the upcoming ML solution will address. We write out a set of requirements, desired objectives and take available data into account, shaping a scope of work and the needed team.

02.

02. Data Collection, Preparation, Feature Selection and Engineering

We’re now gathering the necessary data, which might come from internal sources, external databases, or real-time feeds. Our team starts the process by cleaning and preprocessing the data to remove errors, handle missing values, and format it for analysis. This stage involves selecting the most relevant data attributes (features) that the model will use to learn. Optionally, Devox can perform feature engineering: this practice will create new features from the existing data, enhancing the model's learning capability.

03.

03. Choosing, Training and Evaluating an ML Model

Based on the problem type (e.g., classification, regression, clustering), we select an appropriate ML model. This choice depends on several factors including the size and type of data, the task to be performed, and the computational resources available. Our team then trains it, using a portion of the data set, teaching it to make predictions or decisions, gradually improving its accuracy. After training, the model is evaluated using a different set of data (test data). Key performance metrics like accuracy, precision, recall, and F1 score are used to evaluate its performance.

04.

04. Hyperparameter Tuning and Optimization and Model Deployment

Based on the evaluation results, the model's hyperparameters are adjusted to improve its performance. This process can be automated using techniques like grid search or random search. Once the model performs satisfactorily, it's deployed into a production environment where it can start making predictions or decisions with real-world data.

05.

05. Monitoring and Maintenance

Post-deployment, the model's performance is continuously monitored to ensure it remains accurate over time. As data and environments change, the model may need to be retrained or updated. Our team stays in touch to incorporate this feedback, as learning from the model's performance in the real world is a crucial step. We make adjustments or scale the system at your request.

  • 01. Problem Definition

  • 02. Data Collection, Preparation, Feature Selection and Engineering

  • 03. Choosing, Training and Evaluating an ML Model

  • 04. Hyperparameter Tuning and Optimization and Model Deployment

  • 05. Monitoring and Maintenance

Benefits

Benefits of Machine Learning for Your Business

Understanding machine learning solution comes through understanding what business objectives it can improve. Regardless of the industry you work in, you’ll tackle numerous and most versatile pains: see what you’ll improve.

01

Improve Decision Making and Leverage Predictive Insights

Machine learning analyzes large sets of data to identify trends and patterns, helping you make informed decisions and reducing the reliance on guesswork. Forecast future trends, customer behaviors, and market changes to plan and optimize your business strategy the best way possible.

02

Stand Up to Fraud and Boost Security

Eliminate any threat like information leakage in the bud thanks to solutions like biometric recognition or ML-driven data analysis. Be prepared to repel any attack: you’ll identify fraudulent activities and security breaches by recognizing patterns that indicating suspicious behavior early.

03

Cut Costs Where Necessary

Reduce operational costs by streamlining operations and automating tasks: machine learning solutions reduce the need for manual labor, freeing your specialists to make effort where their unique skills are needed most, and direct budget to what will definitely pay off: insights from ML-processed data will tell you what those directions are.

04

Reach Product and Service Innovation and Get Above Competitors

Machine learning can analyze customer feedback and market trends to assist in developing new and improved products and services. Leverage data-driven insights to reach impeccable service - and gain competitive advantage automatically.

Key Functionalities

Key Functionalities to Add to Your Custom Machine Learning System

01

Learning and Self-Improvement

The core feature of any ML system is its ability to learn from data. Unlike traditional software, which follows explicitly programmed instructions, an ML system improves its performance over time by learning from past experiences or data through techniques like reinforcement learning and feedback.

02

Predictive Analysis

ML systems are often used for predictive analysis. They can forecast future events, trends, or behaviors based on historical data, which is invaluable for decision-making in various domains.

03

Adaptability

ML systems can adapt to new data and changes over time. This flexibility allows them to stay relevant and effective even as the nature of the data or the environment changes.

04

Pattern Recognition

ML systems are adept at identifying patterns and correlations in large datasets that might not be immediately apparent to humans. This is useful in numerous applications, from detecting fraudulent transactions to recommending products to customers.

05

Automation of Decision-Making Processes

ML systems can automate complex decision-making processes by using learned data patterns to make predictions or take actions.

06

Handling of Large and Diverse Data Sets

ML systems are designed to handle vast amounts of data and can process and analyze data from varied sources, including structured, unstructured, and semi-structured data.

07

Customization and Personalization

ML systems can provide personalized experiences to users by learning from individual user data. This is widely used in applications like content recommendation and targeted marketing.

08

Real-Time Data Processing

Many ML systems can process and analyze data in real-time, providing immediate insights and responses, which is crucial in time-sensitive applications.

Case Studies

Our Latest Works

View All Case Studies
Sport Info Solution Sport Info Solution
  • Backend
  • Frontend
  • Cloud
  • Metrics & Data

Sport Analytics Platform

Sports Info Solutions is a sports data provider that focuses on gathering and structuring sports data, its analytics and technology.

Additional Info

Core Tech:
  • .NET Core​
  • MS SQL
  • ELK​
  • Vue.js
  • AWS​
  • Docker
  • DataDog​
  • R
Country:

USA USA

Web 3 White-label PaaS NeoBank Web 3 White-label PaaS NeoBank
  • Web3
  • Fintech

Web 3 White-label PaaS NeoBank

Our client is a blockchain technology firm that has a network of international financial service provider partners. The project is a white-label PaaS ecosystem for neo banking solutions based on the blockchain network.

Additional Info

Country:

USA USA

Social Media Screening Platform Social Media Screening Platform
  • Backend
  • Frontend
  • Cloud Services
  • DevOps & Infrastructure

Social Media Screening Platform

The project is a web-based AI-powered platform for comprehensive social media background screening. Its supertask is to streamline potential employee background checks for companies, tackling employment risk management.

Additional Info

Core Tech:
  • .NET Core
  • Angular
  • Azure
  • Docker
  • GitLab CI/CD
  • Selenium Web Driver
Country:

USA USA

and over 200 our featured partners and clients

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Awards & Certifications

Industry Contribution Awards & Certifications

Check Devox Software Awards on rating & review platforms among top software development companies and Certifications our team members holds.

  • Awards
  • Certifications
  • UpWork

    UpWork

  • Clutch

    Clutch

  • The Manifest

    The Manifest

  • DesignRush

    DesignRush

  • MC.today

    MC.today

  • Clutch

    Clutch

  • Clutch

    Clutch

  • AppFutura

    AppFutura

  • Clutch

    Clutch

  • GoodFirms

    GoodFirms

  • DesignRush

    DesignRush

  • UpWork

    UpWork

  • Professional Scrum Master™ II (PSM II)

    Professional Scrum Master™ II (PSM II)

  • Professional Scrum Product Owner™ I (PSPO I)

    Professional Scrum Product Owner™ I (PSPO I)

  • ITIL v.3 Foundation Certificate in IT Service Management

    ITIL v.3 Foundation Certificate in IT Service Management

  • ITSMS Auditor/Lead Auditor of ISO Standard 20000

    ITSMS Auditor/Lead Auditor of ISO Standard 20000

  • Microsoft Certified: DevOps Engineer Expert

    Microsoft Certified: DevOps Engineer Expert

  • Microsoft Certified: Azure Administrator Associate

    Microsoft Certified: Azure Administrator Associate

  • Quality Assurance ISTQB Foundation Level

    Quality Assurance ISTQB Foundation Level

  • Microsoft Certified Solution Develop (MCSD)

    Microsoft Certified Solution Develop (MCSD)

  • Java Development Certified Professional

    Java Development Certified Professional

  • JavaScript Developer Certificate – W3Schools

    JavaScript Developer Certificate – W3Schools

  • Certified Artificial Intelligence Scientist (CAIS)

    Certified Artificial Intelligence Scientist (CAIS)

  • Oracle Database SQL Certified Associate

    Oracle Database SQL Certified Associate

Testimonials

Testimonials

Sweden

The solutions they’re providing is helping our business run more smoothly. We’ve been able to make quick developments with them, meeting our product vision within the timeline we set up. Listen to them because they can give strong advice about how to build good products.

Carl-Fredrik Linné
Tech Lead at CURE Media
Darrin Lipscomb
United States

We are a software startup and using Devox allowed us to get an MVP to market faster and less cost than trying to build and fund an R&D team initially. Communication was excellent with Devox. This is a top notch firm.

Darrin Lipscomb
CEO, Founder at Ferretly
Daniel Bertuccio
Australia

Their level of understanding, detail, and work ethic was great. We had 2 designers, 2 developers, PM and QA specialist. I am extremely satisfied with the end deliverables. Devox Software was always on time during the process.

Daniel Bertuccio
Marketing Manager at Eurolinx
Australia

We get great satisfaction working with them. They help us produce a product we’re happy with as co-founders. The feedback we got from customers was really great, too. Customers get what we do and we feel like we’re really reaching our target market.

Trent Allan
CTO, Co-founder at Active Place
United Kingdom

I’m blown up with the level of professionalism that’s been shown, as well as the welcoming nature and the social aspects. Devox Software is really on the ball technically.

Andy Morrey
Managing Director at Magma Trading
Vadim Ivanenko
Switzerland

Great job! We met the deadlines and brought happiness to our customers. Communication was perfect. Quick response. No problems with anything during the project. Their experienced team and perfect communication offer the best mix of quality and rates.

Vadim Ivanenko
Jason_Leffakis
United States

The project continues to be a success. As an early-stage company, we're continuously iterating to find product success. Devox has been quick and effective at iterating alongside us. I'm happy with the team, their responsiveness, and their output.

Jason Leffakis
Founder, CEO at Function4
Sweden

We hired the Devox team for a complicated (unusual interaction) UX/UI assignment. The team managed the project well both for initial time estimates and also weekly follow-ups throughout delivery. Overall, efficient work with a nice professional team.

John Boman
Product Manager at Lexplore
Tomas Pataky
Canada

Their intuition about the product and their willingness to try new approaches and show them to our team as alternatives to our set course were impressive. The Devox team makes it incredibly easy to work with, and their ability to manage our team and set expectations was outstanding.

Tamas Pataky
Head of Product at Stromcore
Stan Sadokov
Estonia

Devox is a team of exepctional talent and responsible executives. All of the talent we outstaffed from the company were experts in their fields and delivered quality work. They also take full ownership to what they deliver to you. If you work with Devox you will get actual results and you can rest assured that the result will procude value.

Stan Sadokov
Product Lead at Multilogin
United Kingdom

The work that the team has done on our project has been nothing short of incredible – it has surpassed all expectations I had and really is something I could only have dreamt of finding. Team is hard working, dedicated, personable and passionate. I have worked with people literally all over the world both in business and as freelancer, and people from Devox Software are 1 in a million.

Mark Lamb
Technical Director at M3 Network Limited
FAQ

FAQ

  • What industries can benefit most from Machine Learning Development services?

    So far, artificial intelligence and machine learning services are helping most in industries like healthcare, finance & banking, retail, manufacturing, e-commerce, transportation and logistics, telecommunications, energy, agriculture, education, marketing & advertising. Each industry has unique applications tailored to its specific challenges, and Devox can help you develop a customized software.

  • What programming languages and technologies do you use for Machine Learning Development?

    We primarily use Python for its extensive libraries like TensorFlow, PyTorch, and scikit-learn, which are ideal for ML development. For big data processing, we utilize Apache Spark, and for cloud-based solutions, we employ AWS and Azure ML services. This tech stack ensures robust, scalable, and efficient ML solutions.

  • How long does machine learning development take?

    The time it takes to develop a Machine Learning (ML) project varies widely. Simple projects with clear objectives and readily available data can take a few weeks to a couple of months. More complex projects, involving large datasets and sophisticated algorithms, might take several months to over a year. The key factors influencing this timeline include the complexity of the ML task, the quality and availability of data, the intricacies of model training and tuning, and the integration process with existing systems. Additionally, the expertise of the development team and the computational resources available can significantly impact the development speed.

  • How is the process of ML development different from SDLC?

    Machine Learning (ML) development differs from traditional Software Development Life Cycle (SDLC) mainly ints focus on data and model iteration.

    In ML, a significant portion of the process involves collecting, processing, and analyzing data, unlike in traditional software development where the emphasis is on meeting specific functional requirements. ML projects are characterized by extensive experimentation and tuning of models, making them more iterative and less predictable.

    Success in machine learning solutions architect is measured by specific performance metrics like accuracy and precision, whereas traditional software success is assessed based on functionality and user satisfaction. Additionally, deploying an ML model requires ongoing monitoring and updates to maintain its effectiveness, a step that’s typically less intensive in conventional software.

  • Can you integrate Machine Learning solutions with existing business systems?

    Yes, Machine Learning (ML) solutions can be integrated with existing business systems. The integration process involves first understanding your current system’s architecture and data flow. We then establish data pipelines to feed relevant data from your systems to the ML models. This is often achieved using APIs or developing microservices to ensure seamless communication between the ML solution and your existing software

    Once integrated, the ML system can enhance your current setup by providing advanced data analysis, predictive insights, and automation capabilities. Continuous monitoring and adjustments are made post-integration to ensure optimal performance and compatibility with your business processes.

  • What are machine learning practice problems and solutions?

    Machine learning practice problems and solutions involve applying ML algorithms to real-world scenarios to gain practical skills. Common problems include classification tasks like email spam detection, regression tasks such as predicting housing prices, and clustering for customer segmentation.

    Solutions require selecting appropriate algorithms, processing and analyzing data, and training and testing models. For instance, in spam detection, a model is trained on a dataset of labeled emails to classify them as spam or not. In all cases, the effectiveness of a solution is evaluated based on its accuracy, efficiency, and ability to generalize from training data to real-world situations.

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