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And a report by the European Union Agency for the Space Programme predicts that the insurance and finance industry will become the top consumer of Earth observation data and services over the next decade — resulting in more than $1 billion in total revenue by 2031. The company uses NVIDIA GPUs for both training and inference.
billion by 2031. It is projected to grow at a CAGR of 34.20% in the forecast period (2024-2031). Additionally, many datasets include categorical variables , which must be transformed into numerical values for models to process them correctly. The global Machine Learning market continues to expand. It was valued at USD 35.80
billion by 2031 at a CAGR of 34.20%. After cleaning, the data may need to be preprocessed, which includes scaling numerical features, encoding categorical variables, and transforming text or images into formats suitable for the model. converting dates into day of the week, creating dummy variables for categorical data).
billion by 2031 at a CAGR of 34.20%. CatBoost CatBoost, developed by Yandex, handles categorical data without extensive preprocessing. Ensemble learning plays a critical role in driving innovation. The global Machine Learning market was valued at USD 35.80 billion in 2022 and is projected to grow to USD 505.42
billion by 2031, growing at a CAGR of 34.20%. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding. A Machine Learning Engineer is crucial in designing, building, and deploying models that drive this transformation.
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