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Machine Learning (ML)

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Machine learning (Machine Learning) is a technology thanks to which programs learn to solve problems independently by analyzing large arrays of data. Instead of the programmer writing clear rules "if A, then B", the algorithm itself finds these rules based on previous experience.

What is Machine Learning?

ML is the foundation of modern artificial intelligence. If a regular program operates according to a rigid algorithm, then the ML model looks for regularities.

Three main types: • Learning with a teacher - the algorithm receives data with correct answers (for example, a photo with the captions "cat" and "dog") • Learning without a teacher - the algorithm itself looks for structure in unlabeled data (for example, customer segmentation) • Reinforcement learning - the algorithm learns by trial and error, receiving a "reward" for correct actions

It is ML that determines what you will see in the Instagram feed and which product Amazon will recommend to you.

How does Machine Learning work?

The process consists of stages: data collection → preparation (cleaning) → model selection → training on the training set → testing → deployment. The more quality data, the more accurate the result.

Options for using ML

01Recommender systems

Netflix and Spotify use ML for content recommendations. This increases user retention.

02Demand forecasting

Retail uses ML to forecast sales and optimize inventory balances.

03Antifraud

Banks analyze thousands of transactions per second, detecting anomalies and blocking fraud.

04Dynamic pricing

Uber or airlines change prices in real time based on demand, weather and time.

/ FAQ

AI is the general concept of intelligent machines. ML is a concrete way to achieve AI through learning from data.

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Machine Learning (ML)
/ Machine Learning (ML)

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