Vizuara Books
Foundations for AI & ML
The math and code every AI/ML career stands on.
Build the four pillars of machine learning from the ground up: linear algebra, probability, calculus, and Python. Then put them to work training a neural network and touring the core ML algorithms, one hand-illustrated chapter at a time.
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00Getting Started3 capsules
Getting Started — 3 chapters.
01Why Foundations Matterconceptfree14 min02The Map: AI, ML, and Deep Learningconcept🔒13 min03How a Model Learns: The Big Pictureintuition🔒13 min01Linear Algebra for ML6 capsules
Linear Algebra for ML — 6 chapters.
04Matrix-Vector Multiplication as a Transformationmath🔒12 min05The Dot Product as a Linear Transformationmath🔒12 min06Linear Transformations in 3D and Dimensionality Changemath🔒13 min07The Determinant: What It Measuresintuition🔒12 min08Determinants Deeper: Invertibility and Collapsedeep-dive🔒12 min09Eigenvalues and Eigenvectors, Intuitivelyintuition🔒12 min02Probability & Statistics4 capsules
Probability & Statistics — 4 chapters.
10Conditional Probability and Bayes' Theoremmath🔒12 min11Probability Distributions for MLconcept🔒13 min12The Naive-Bayes Classifiercode🔒12 min13Evaluating a Model: Accuracy, Precision, Recallconcept🔒12 min03Calculus for Optimization3 capsules
Calculus for Optimization — 3 chapters.
14Differential Calculus: Derivatives and Gradientsmath🔒13 min15The Chain Rule and Backpropagationdeep-dive🔒14 min16Integral Calculus Foundations for MLmath🔒13 min04Python & the ML Toolkit7 capsules
Python & the ML Toolkit — 7 chapters.
17Introduction to Python for MLcode🔒13 min18Classes and Objects in Pythoncode🔒13 min19NumPy: Arrays and Vectorized Computationcode🔒14 min20Pandas for Data Wranglingcode🔒12 min21Data Visualization for Machine Learningcode🔒13 min22Scikit-learn: The ML Workhorsecode🔒13 min23Deep Learning Libraries: TensorFlow and PyTorchcode🔒14 min05Optimization & Neural Networks6 capsules
Optimization & Neural Networks — 6 chapters.
24A Neural Network from Scratchproject🔒11 min25Gradient Descent and Backpropagationmath🔒14 min26Stochastic Gradient Descentconcept🔒14 min27Momentum-Based Gradient Descentconcept🔒12 min28RMSprop and Adamdeep-dive🔒14 min29Core ML Algorithms: A Tourconcept🔒16 min06Putting It Together2 capsules
Putting It Together — 2 chapters.
30The Evolution and Future of AI/MLconcept🔒13 min31Capstone: From Foundations to a First Modelproject🔒13 minRatings & reviews
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