Simple, plain-English explanations accompanied by math, code, and real-world examples. — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) Roadmap Part 1: Why Machine Learning Matters. The big picture of artificial intelligence and machine learning — past, present, and future. Part 2.1: Supervised Learning. Learning with an answer key. …

A compendium of resources for crafting a curriculum on artificial intelligence, machine learning, and deep learning. — This article is an addendum to the series Machine Learning for Humans 🤖👶, a guide for getting up-to-speed on machine learning concepts in 2-3 hours. General advice on crafting a curriculum Going to school for a formal degree program for isn’t always possible or desirable. For those considering an autodidactic alternative, this is for you.

Exploration and exploitation. Markov decision processes. Q-learning, policy learning, and deep reinforcement learning. — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) “I just ate some chocolate for finishing the last section.” In supervised learning, training data comes with an answer key from some godlike “supervisor”. If only life worked that way!

Where, why, and how deep neural networks work. Drawing inspiration from the brain. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Real-world applications. — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) With deep learning, we’re still learning a function f to map input X to output Y with minimal loss on the test data, just as we’ve been doing all along. Recall our initial “problem…

Clustering and dimensionality reduction: k-means clustering, hierarchical clustering, principal component analysis (PCA), singular value decomposition (SVD) — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) How do you find the underlying structure of a dataset? How do you summarize it and group it most usefully? How do you effectively represent data in a compressed format? …

Non-parametric models: k-nearest neighbors, decision trees, and random forests. Introducing cross-validation, hyperparameter tuning, and ensemble models. — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) Non-parametric learners. Things are about to get a little… wiggly. In contrast to the methods we’ve covered so far — linear regression, logistic regression, and SVMs where the form of the model was pre-defined — non-parametric…

Classification with logistic regression and support vector machines (SVMs). — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) Classification: predicting a label Is this email spam or not? Is that borrower going to repay their loan? Will those users click on the ad or not? Who is that person in your Facebook picture? Classification predicts a…

The two tasks of supervised learning: regression and classification. Linear regression, loss functions, and gradient descent. — This series is available as a full-length e-book! Download here. Free for download, contributions appreciated (paypal.me/ml4h) How much money will we make by spending more dollars on digital advertising? Will this loan applicant pay back the loan or not? What’s going to happen to the stock market tomorrow?

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