Machine Learning Basics makes one of the most powerful and in-demand technologies approachable for beginners. This eBook explains machine learning concepts intuitively and then shows you how to implement them using scikit-learn in Python.
From understanding data and features to training, evaluating, and deploying models, every topic is covered with clarity and practical examples.
Topics covered
- Supervised vs. unsupervised learning
- Linear regression, decision trees, and random forests
- Feature engineering and data preprocessing
- Model evaluation: accuracy, precision, recall, F1
- Intro to neural networks and deep learning
Instant PDF download. Python code with scikit-learn examples.