Understanding Machine Learning and the ML Pipeline — Step by Step

1. 1Define Machine Learning as a subset of AI where machines learn from data
2. 2Identify the key concept of ML as learning from examples to make predictions
3. 3Apply the ML pipeline by collecting data, preprocessing it, training a model, and evaluating its performance
4. 4Use simple examples like image classification to illustrate the concept of ML
5. 5Explore the different stages of the ML pipeline, including data preparation, model selection, and deployment

Data scientists and machine learning engineers can benefit from this article to understand the fundamentals of ML and its pipeline, and apply it to their projects

💡 Machine Learning is a subset of AI that enables machines to learn from data and make predictions without being explicitly programmed

🤖 Learn how machines learn from data with Machine Learning! 📊