Neural Networks & Deep Learning
Master neural networks from the ground up — including feedforward networks, CNNs, RNNs, training techniques, regularization, and applied deep learning in sports analytics and betting models.
9 chapters across 3 books
Neural Networks from Scratch
AI Engineering
Training Deep Networks
AI Engineering
Regularization & Generalization
AI Engineering
Convolutional Neural Networks
AI Engineering
Recurrent Neural Networks
AI Engineering
Autoencoders & Representation Learning
AI Engineering
Generative Adversarial Networks
AI Engineering
Neural Networks for Betting
Sports Betting
Deep Learning for Soccer
Soccer Analytics
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Machine Learning 18 chapters Python for Data Science 8 chapters Probability & Statistics 15 chapters Sports Betting Analytics 16 chapters Natural Language Processing (NLP) 12 chapters Data Visualization 9 chapters Sports Analytics 14 chapters Predictive Modeling & Forecasting 17 chapters Computer Vision 8 chapters AI-Assisted Software Development 12 chapters AI Agents & Autonomous Systems 6 chapters Software Engineering Best Practices 11 chapters AI Ethics & Governance 18 chapters Cybersecurity & Ethical Hacking 17 chapters Applied Psychology 16 chapters Python for Business 15 chapters Working with AI Tools 12 chapters Creator Economy & Digital Entrepreneurship 11 chapters Data Governance & Privacy 12 chapters Conflict Resolution & Communication 9 chapters Fan Studies & Internet Culture 11 chapters Luck, Probability & Decision-Making 10 chapters Home Systems & Maintenance 9 chapters Regulatory Technology & Compliance 10 chapters AI & Machine Learning for Business 10 chapters COBOL Programming 10 chapters Political Analytics & Data 10 chapters Propaganda & Disinformation 9 chapters Psychology of Attraction & Relationships 9 chapters AI Literacy & Education 13 chapters Computer Science Fundamentals 10 chapters Surveillance, Privacy & Digital Rights 12 chapters Algorithms & Their Impact on Society 8 chapters Learning Science & Metacognition 20 chapters Systems Thinking & Mental Models 20 chapters Mainframe & COBOL Programming 14 chapters Database Systems 13 chapters Statistics & Probability 14 chapters Data Science Fundamentals 14 chapters Cognitive Science & Critical Thinking 13 chapters Learning Science & Study Skills 14 chapters Quantum Physics & Wave Mechanics 12 chapters Appalachian Studies 12 chapters Epistemic Failure & How Knowledge Goes Wrong 13 chapters