Machine Learning means teaching AI to solve complex problems. There are Unsupervised Learning, Reinforcement Learning, and supervised Machine Learning; algorithms are chosen according to the task.
We offer all kinds of services for your Machine Learning project, studying business goals and selecting appropriate tools to solve the defined problem.
Deep learning
Examining a data set very deeply with algorithms to discover more valuable information for a business.
Predictive algorithms
Using ML to analyze the data that help make accurate predictions about a company's activity and outcomes.
Smart chatbots
A part of Machine Learning development that allows companies to use modern technology to improve customer experience.
Natural language processing
Analyzing human language data, in both forms – text and voice, to get valuable information and find business insights.
Real-time data analytics
Using Machine Learning algorithms to gather and analyze information as quickly as possible.
Computer vision
Developing a Machine Learning project to analyze images and videos to compare or extract valuable information quickly.
Expert systems
Using different types of Machine Learning to build recommendation software, diagnosis tools and other expert systems.
Our company employs officially certified Artificial Intelligence and Machine Learning engineers. Let’s schedule a call to discuss your project with real experts!
Companies from different countries and industries choose us as an experienced and trusted Machine Learning development company that offers profound expertise combined with real-world vision.
5+ Years
in software development
We know how to use ML technology to optimize and automate business processes and introduce innovation.
100+
experienced engineers
With us, you can find a proficient Machine Learning developer for your ML project of any complexity.
~85%
are senior specialists
ML specialists at Fively work with sophisticated machine learning models and algorithms to bring precise results.
50+
successful projects
You can rely on us in any ML projects related to customer experience, fraud detection, and other important areas.
We use modern tools and relevant programming languages to build reliable solutions for our clients. It is important to select the right tech stack for complex and simple Machine Learning projects.
Backend
Frontend
Cloud
Database
AI and ML
We established an effective multi-step approach that we use for each Machine Learning project, which allows us to bring quicker and more precise results for a client.
We provide Machine Learning development services for companies from various industries. Our team always starts with interviewing a client about their business specifics and challenges.
InsurTech
Improve client base management with bespoke insurance automation tools.
HealthTech
Safeguard public health with creative technologies.
FinTech
Even traditional industries require a modern approach.
Cyber Security
Modern tech is a good basis for safe and sustained development.
eCommerce
Get a custom solution to boost your retail business.
Real Estate
Bespoke apps are to change the face of the real estate industry.
Bring new opportunities to analyze data, monitor actions in real time, improve various processes – everything you want becomes possible with Machine Learning app development.
Fively is a custom software development company, that has been gaining recognition throughout its existence.
Let's have a call and discuss your custom solution.
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ML or Machine Learning is an area of computer science and AI-related technologies. In short, it deals with teaching a machine to analyze huge amounts of data and give certain results, such as suspicious activity detection, error correction, image recognition, etc. ML developers use different Machine Learning algorithms to pursue these goals, and it takes knowledge and experience to select the right algorithm and teach the system. The use of Machine Learning in tech allows software to be more precise in making predictions about certain outcomes, which is the main goal of teaching.
Machine Learning development can significantly help companies from the number of industries, such as:
There are the 4 basics of machine learning that include reinforcement learning, as well as semi-supervised, unsupervised and supervised Machine Learning. These four approaches are also known as types of Machine Learning models. They allow specialists to cover most tasks and problems, including pattern discovery and predictions. As a Machine Learning development company, we use supervised Machine Learning and other types to solve challenges for our clients’ projects in various industries.
AI development services include ML, but there is a significant difference between the two. Artificial Intelligence focuses on the idea that computer systems can mimic human thinking to solve problems faster and error-free. Machine Learning is about teaching computer systems how to perform certain tasks, identify patterns, and always give accurate results.
A model is a kind of file that ML specialists create and teach to recognize specific behavior or elements. Training data is very important because it can make a model correct and fast in analyzing. A data set for training should be big and diverse enough, especially when your aim is to deal with complicated problems like fraud detection.
As their names suggest, the first type doesn’t include much human involvement while the second type depends on certain actions from a specialist. There are different types of data sets in ML. If you are an experienced Machine Learning developer you know that you need labeled data to build supervised learning algorithms. Correspondingly, unsupervised learning will require only unlabeled data.
Specialists use three primary ML techniques: regression, clustering, and classification. The first one means the continuous response from the system. In the second and third one, you can see specific clusters and classes.
There are lots of ML algorithms related to techniques and methods like regression, clustering, and classification. For example, a neural network that resembles the human brain can relate both to clustering and regression. Other widely used algorithms include linear regression, binary classification, K-means, dimensionality reduction, and more.
There are many factors that may influence this choice. The most important one is the type of your project. Next factor is how much time you have – experts in Machine Learning modeling need to quickly evaluate the speed of training and decide on the right model for this particular project. Performance of the chosen algorithm is also a critical factor, because it should bring as correct results as possible.
Python is the most widely used programming language for AI and ML. Moreover, data scientists often work with Java, C++, Haskell, Prolog, and other programming languages. The choice of languages and tools depends on your goals and sometimes on the history of what developers working on this project applied previously.
Cloud computing and ML development are the areas that can be very beneficial for each other. Cloud environments provide almost unlimited opportunities to store large volumes of information. How is it connected to ML? Typically, you need a lot of training data to start a new Machine Learning project – and the best way to have access to this data is to keep it in the cloud. The reason why so many companies opt for AWS and Google Cloud migration is because they want to use all the advantages of AI and ML. On the other hand, different types of machine learning can provide more opportunities for cloud software development and testing – predictive analytics, neural networks, computer vision, and other technologies may increase efficiency, reduce bugs, and help specialists’ work.
If you want to become a Machine learning specialist, there are some good ML projects that you can try to develop. We can give you a few examples:
The cost of ML engineering may depend on three main factors:
The ideal team for ML project development should include:
However, real world situations may differ – for example, a smaller and less complicated project won’t require such a diverse team. When you search for a ML technology partner, it is important to start with business analytics and define the core features that should be in your solution. Understanding the real complexity of the project, you will be able to select the right team for it. If you are not sure how to estimate the scope of work or choose the ML specialist level, just reach out and talk to us.
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