AI and Machine Learning

A Business Users Introduction to Machine Learning (ML)

A business users Introduction to the basic concepts of machine learning and how they work.

JP Lorandi
December 7, 2022
illustration for outsourcing

What is Machine Learning

Machine learning uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with experience.

This learning is achieved through the construction of models from a set of training data, which can then be used to make predictions about future data.

There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.

Supervised learning is where the machine learning algorithm is given a set of training data (i.e., input/output pairs) and asked to learn a function that maps the input to the output.

Unsupervised learning is where the machine learning algorithm is given a set of training data but not told what the desired output should be. The algorithm must then learn to find some structure in the data (e.g., groups of similar data points).

Reinforcement learning is where the machine learning algorithm is given a goal but not told how to achieve it. The algorithm must then learn by trial and error what actions will lead to the desired goal.

Machine learning algorithms can be deployed in a number of ways, including as standalone program or as part of a larger system. They can also be deployed in physical devices, such as self-driving cars, or in virtual environments, such as online recommendation systems.

Machine learning algorithms and models

ML models are algorithms that parse data, learn from that data, and make predictions about new data. ML is a subset of AI, and both ML and AI are terms for a large umbrella of computational methods.

There are many ML models, but some of the most well-known are linear regression, logistic regression, decision trees, Support Vector Machines, and Neural Networks.

Each ML model has its own strengths and weaknesses, so choosing the right model is essential for getting accurate predictions.

ML models can be trained on data sets of varying sizes, but the larger the data set, the more accurate the predictions will be. When training an ML model, it's important to split the data into a training set and a test set. The training set is used to train the model, while the test set is used to evaluate the performance of the model. If the model performs well on the test set, then it's likely to generalize well to new data.

ML is an iterative process, so even if a model doesn't perform well at first, it can be improved by tweaking the algorithms or changing the data set.

Popular applications of machine learning

Machine learning is a rapidly growing field with immense potential for businesses. Its applications are far-reaching and varied, limited only by our imagination. Some popular machine learning use cases include predictive maintenance, demand forecasting, and fraud detection, among many others.

Let's cover a handful of ML use cases below:

Predictive maintenance is a machine learning technique that can be used to detect equipment failures before they happen. By monitoring data from sensors and other sources, machine learning algorithms can develop a deep understanding of how equipment operates over time. This knowledge can be used to identify patterns that indicate an impending failure, allowing businesses to take preventive action and avoid costly downtime.

Demand forecasting is another important application of machine learning. This technique can be used to predict future demand for products or services, based on historical data and other factors. Businesses can use demand forecasts to optimize inventory levels, staff their operations, and plan marketing campaigns.

Many companies leverage machine learning for fraud detection and it is making a big impact on the bottom line. By analyzing data from transactions, machine learning algorithms can learn to identify patterns that are indicative of fraudulent activity. This knowledge can be used to flag suspicious transactions in real-time, helping businesses to protect themselves from fraudsters.

Other popular machine learning applications in business include text classification, image recognition, and customer segmentation.

Text classification is the process of automatically assigning labels to pieces of text, such as emails or social media posts. The machine learning algorithm looks at a set of training data, where each piece of text is already labeled with the correct category, and tries to learn how to label new pieces of text.

Image recognition is a machine learning technology that enables computers to identify objects in digital images. By “objects,” we mean things like people, animals, buildings, and so on. This technology is used in a variety of applications, such as security and surveillance, medical image analysis, and self-driving cars.

Customer segmentation is the process of dividing customers into groups based on shared characteristics, such as demographics or behavior. This information can be used to better understand customer needs and target marketing efforts.

A quick Double Click

One of the most interesting topics in machine learning is reinforcement learning. This is a type of learning where an agent learns by taking actions in an environment and receiving feedback based on those actions.

The goal is for the agent to learn how to take the best possible actions in order to maximize some goal or reward.

Reinforcement learning has been used to develop successful strategies for a variety of tasks, including game playing, resource management, and robotic control.

It is an active area of research with many open problems, and it promises to have a significant impact on artificial intelligence in the future.

Machine learning is a powerful tool that can be used to improve the accuracy of predictions and make better decisions. However, it is important to remember that machine learning is only as good as the data that is used to train it.

In order to get the most out of machine learning, organizations need to invest in quality data and have a team of experts who can manage and interpret the results. With the right data and expertise, machine learning can help organizations achieve their goals and stay ahead of the competition.

No items found.

We are Azumo
and we get it

We understand the struggle of finding the right software development team to build your service or solution.

Since our founding in 2016 we have heard countless horror stories of the vanishing developer, the never-ending late night conference calls with the offshore dev team, and the mounting frustration of dealing with buggy code, missed deadlines and poor communication. We built Azumo to solve those problems and offer you more. We deliver well trained, senior developers, excited to work, communicate and build software together that will advance your business.

Want to see how we can deliver for you?

schedule my call

Benefits You Can Expect

Release software features faster and maintain apps with Azumo. Our developers are not freelancers and we are not a marketplace. We take pride in our work and seat dedicated Azumo engineers with you who take ownership of the project and create valuable solutions for you.

Industry Experts

Businesses across industries trust Azumo. Our expertise spans industries from healthcare, finance, retail, e-commerce, media, education, manufacturing and more.

Illustration of globe for technology nearshore software development outsourcing

Real-Time Collaboration

Enjoy seamless collaboration with our time zone-aligned developers. Collaborate, brainstorm, and share feedback easily during your working hours.

vCTO Solution Illustration

Boost Velocity

Increase your development speed. Scale your team up or down as you need with confidence, so you can meet deadlines and market demand without compromise.

Illustration of bullseye for technology nearshore software development outsourcing

Agile Approach

We adhere to strict project management principles that guarantee outstanding software development results.

Quality Code

Benefits from our commitment to quality. Our developers receive continuous training, so they can deliver top-notch code.

Flexible Models

Our engagement models allow you to tailor our services to your budget, so you get the most value for your investment.

Client Testimonials


Azumo has been great to work with. Their team has impressed us with their professionalism and capacity. We have a mature and sophisticated tech stack, and they were able to jump in and rapidly make valuable contributions.

Drew Heidgerken
Director of Engineering

We worked with Azumo to help us staff up our custom software platform redevelopment efforts and they delivered everything we needed.

James Wilson
Discovery Channel

The work was highly complicated and required a lot of planning, engineering, and customization. Their development knowledge is impressive.

Discovery Channel
Costa Constantinou
Senior Product Manager

Azumo helped my team with the rapid development of a standalone app at Twitter and were incredibly thorough and detail oriented, resulting in a very solid product.

Seth Harris
Senior Program Manager

So much of a successful Cloud development project is the listening. The Azumo team listens. They clearly understood the request and quickly provided solid answers.

Matt Sutton
Head of Product
Bento for Business

Azumo came in with a dedicated team that quickly grasped our problem and designed and built our data integration solution. They delivered a clearer picture for our business in a timeframe I didn’t think was possible.

Bento for Business
Sean Anderson
Chief Operating Officer

How it Works

schedule my call

Step 1: Schedule your call

Find a time convenient for you to discuss your needs and goals

Step 2: We review the details

We estimate the effort, design the team, and propose a solution for you to collaborate.

Step 3: Design, Build, Launch, Maintain

Seamlessly partner with us to confidently build software nearshore

We Deliver Every Sprint

Icon illustrating the advantage of time zone-aligned software developers from Azumo, ensuring work hours synchronized with client schedules.

Time Zome Aligned

Our nearshore developers collaborate with you throughout your working day.

Icon showcasing the advantage of hiring expert engineers from Azumo for software development services.

Experienced Engineers

We hire mid-career software development professionals and invest in them.

Icon symbolizing how Azumo's software developers prioritize honest, English-always communication for building quality software.

Transparent Communication

Good software is built on top of honest, english-always communication.

Icon representing how Azumo's developers enhance velocity by approaching software development with a problem solver's mindset.

Build Like Owners

We boost velocity by taking a problem solvers approach to software development.

Icon illustrating how Azumo's quality assurance process ensures the delivery of reliable, working code for every project.

Expect Consistent Results

Our internal quality assurance process ensures we push good working code.

Icon depicting how Azumo follows strict project management principles to stay aligned with your goals throughout the development process.

Agile Project Management

We follow strict project management principles so we remain aligned to your goals