Decoding the Basics: A Comprehensive Review of Oliver Theobald's 'Machine Learning for Absolute Beginners'
Theobald, O. (2021). Machine learning for absolute beginners: A plain English introduction (2nd ed.). Independently Published. 166 pages. ISBN: 9781704409770 Buy the Book here General Overview of the Book 1. Provides an introduction to basic concepts in machine learning including key terms, general workflow, and statistical foundations. 2. Discusses major categories of machine learning like supervised, unsupervised, semi-supervised, and reinforcement learning. 3. Covers important algorithms like linear regression, logistic regression, k-NN, k-means clustering, neural networks, decision trees, ensemble modeling. 4. Explains key aspects like model evaluation, bias-variance tradeoff, regularization, cross-validation. 5. Compares strengths and limitations of different algorithms. For example, tradeoffs between interpretability vs performance. 6. Goes over data preprocessing techniques like feature selection, one-hot encoding, normalization, handling missing values. 7. Uses