Machine Learning and Random Forest Classification

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An overview of machine learning, two popular types of ML, and random forest classification, a popular ML model used by data scientists …

Here are highlights from article Machine Learning and Random Forest Classification

1. Machine learning:
– Predictive insights from ML models help make better decisions and recommendations
– ML models use historical data to make predictions
– ML models can be used in various systems like Salesforce, Commerce Cloud, and Data Cloud

2. Types of machine learning:
– Supervised learning: Uses labeled data to train algorithms with known answers
– Unsupervised learning: Uses unlabeled data to find patterns and structure

3. Random forest classification:
– Popular ML model that uses multiple decision trees to reach a single outcome
– Versatile in handling classification and regression problems
– Effective for estimating missing values in data

4. Importance of choosing the right AI model:
– Understanding different types of AI models helps in selecting the best model for a business problem
– Generative AI and LLMs are not the only options, machine learning offers powerful capabilities

5. Benefits of using ML models:
– ML models can provide personalized recommendations and improve customer experience
– Can be used in various industries and systems to solve complex problems and make accurate predictions

You can read it here: https://sfdc.blog/WPQWz

Source from developer(dot)salesforce(dot)com

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