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Our Skills

Machine learning

Machine learning is a subset of AI that allows systems to automatically learn and improve from experience without explicit programming. Machine learning uses different algorithms, such as neural networks (which we’ll discuss later) to solve problems.

Deep learning

Deep learning is a specific type of machine learning that imitates the way humans obtain particular knowledge. It is an important component of data science and includes statistics and predictive analytics. Examples of deep learning include face recognition, virtual assistants and vision enablement for driverless cars.

Neural network architectures

Neural networks make up part of the deep learning process and are inspired by the structure of the human brain. They are complex structures created from artificial neurons that can process multiple inputs and produce a singular output. Understanding this architecture is essential for deep learning.

Computer vision

Computer vision involves training computers to understand and interpret the visual world. This includes accurately identifying and locating objects, then reacting to what they see through the use of digital images from deep learning models, videos and cameras.

Programming languages and intelligence

Learning specific programming languages is essential for work in the AI field. Python, R, Java and C++ are the most commonly sought after.

Python

Python is one of the most popular programming languages in use at the moment. It was created in 1991, and has since been one of the most widely used programming languages, alongside Java and C++.

It is useful for AI because it is reliable, simple to use and increases execution time. Python requires the least code compared to other languages and has pre-built libraries for scientific computation, advanced computing and machine learning.

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