With Infer, you can develop an application in any artificial intelligence area, including, but not limited to, statistical modeling, classification, regression, clustering, anomaly detection, association rules, computer vision, natural language processing, speech recognition, chatbot, and recommendation systems.
Our machine learning services are complemented by end-to-end product design and world-class software development for a comprehensive and holistic client experience.
Infer team use machine learning tools and algorithms to help companies develop AI-driven products and solutions. Infer team has profound knowledge and experience in designing, implementing and integrating Artificial Intelligence solutions within the customer’s business environment.
Traditional machine learning and deep learning
We help you discover insights in your data and help automate your processes using machine learning.
Machine learning frameworks
We work with all open source machine learning frameworks like Tensorflow, Scikit-learn, Keras, Caffe, MLlib, and others.
AWS, Azure, and Google cloud
It does not matter which cloud platform you have or if you still using your private cloud, we build ML models and deploy them on any platform.
Chatbots are a big use case of machine learning and AI. It can help your organization in level 1 and level 2 support within your organization or client facing. We can build chatbots using open source tools and deploy within your infrastructure in no time.
Machine learning FAQ
What is the difference between artificial intelligence and machine learning?
Artificial intelligence (AI) and machine learning (ML) have often been used interchangeably, even though they refer to different concepts. Artificial intelligence, in short, is the science that explores simulation of intelligent behavior in machines to train them to perform tasks that mimic human activity. Machine learning, on the other hand, is the practical application of AI concepts. We see ML solutions in products and services we use every day.
What is machine learning used for?
At its core, machine learning is about using data to answer questions. Thanks to its ability to process huge amounts of data without the need for human intervention, machine learning has been applied in a number of industries, from healthcare to aviation. We see and interact with ML-driven solutions of varying complexity in products and services we use every day, from searching for information on Google to applying for a bank loan to tracking how many steps you have taken in a day with a body-worn pedometer.
How can AI improve your business?
AI fulfils a wide range of roles in business, and this ubiquity creates a space for each company to take advantage of its potential. Regardless of the industry you operate in, making use of ML-powered solutions will help you automate routine and repetitive tasks so that your employees can use their time to provide a high-value contribution to the business. They can also reduce your operational costs and help you achieve a higher level of efficiency, as well as add innovative features that would not have been feasible without AI, such as a 24/7 customer service chatbot. Most importantly, customized ML that responds closely to your unique business needs will help you stay ahead of the curve and gain a competitive edge over other companies in your sector.
What is machine learning?
Machine learning is not a new concept—many algorithms have been around for a long time. As early as in 1947, Alan Turing gave a talk at the London Mathematical Society, in which he declared that “what we want is a machine that can learn from experience.” However, the concept has gained fresh momentum in the last decade when its development has accelerated exponentially. In essence, machine learning, as a subset of artificial intelligence, describes the way that we give machines access to data and let them learn for themselves. Machine learning models are not explicitly programmed by humans: they find patterns in the data they are given, just like humans would do, and then make decisions based on them.
How do you know what machine learning solutions you should apply?
It’s often said that machine learning is part art and part science. When you look for an ML model to fit your unique business needs, it’s never a matter of just picking the right algorithm. There are several factors that need to come together to create the perfect solution. Certain problems, due to their universal nature, can be addressed using elements available in existing, open-source libraries. Others, however, require a more individual approach and an end-to-end design. To identify the best machine learning model for your business, you will need to work closely with an AI/ML expert to help them understand your goals so that they can advise you on the most suitable solutions.