![]() |
Calculus for Machine Learning LiveLessons - Druckversion +- Forum Rockoldies (https://rockoldies.net/forum) +-- Forum: Fotobearbeitung - Photoshop (https://rockoldies.net/forum/forumdisplay.php?fid=16) +--- Forum: E-Learning, Tutorials (https://rockoldies.net/forum/forumdisplay.php?fid=18) +--- Thema: Calculus for Machine Learning LiveLessons (/showthread.php?tid=19280) |
Calculus for Machine Learning LiveLessons - Panter - 31.01.2021 ![]() LiveLessons - Calculus for Machine Learning WEBRip | English | MP4 + Project Files | 1280 x 720 | AVC ~4033 kbps | 30 fps AAC | 317 Kbps | 48.0 KHz | 2 channels | 06:13:39 | 10.9 GB Genre: eLearning Video / Development, Machine Learning, Calculus Much of machine learning is built around the idea of loss functions and optimizing for them. To understand them, you first need to understand Calculus. Table of Contents 1 Calculus for Machine Learning LiveLessons (Video Training) - Introduction 2 Topics 3 1.1 Differential versus Integral Calculus 4 1.2 A Brief History 5 1.3 Calculus of the Infinitesimals 6 1.4 Modern Applications 7 Topics 8 2.1 Continuous versus Discontinuous Functions 9 2.2 Solving via Factoring 10 2.3 Solving via Approaching 11 2.4 Approaching Infinity 12 2.5 Exercises 13 Topics 14 3.1 Delta Method 15 3.2 The Most Common Representation 16 3.3 Derivative Notation 17 3.4 Constants 18 3.5 Power Rule 19 3.6 Constant Product Rule 20 3.7 Sum Rule 21 3.8 Exercises 22 Topics 23 4.1 Product Rule 24 4.2 Quotient Rule 25 4.3 Chain Rule 26 4.4 Exercises 27 4.5 Power Rule on a Function Chain 28 Topics 29 5.1 Introduction 30 5.2 Autodiff with PyTorch 31 5.3 Autodiff with TensorFlow 32 5.4 Directed Acyclic Graph of a Line Equation 33 5.5 Fitting a Line with Machine Learning 34 Topics 35 6.1 Derivatives of Multivariate Functions 36 6.2 Partial Derivative Exercises 37 6.3 Geometrical Examples 38 6.4 Geometrical Exercises 39 6.5 Notation 40 6.6 Chain Rule 41 6.7 Chain Rule Exercises 42 Topics 43 7.1 Single-Point Regression 44 7.2 Partial Derivatives of Quadratic Cost 45 7.3 Descending the Gradient of Cost 46 7.4 Gradient of Mean Squared Error 47 7.5 Backpropagation 48 7.6 Higher-Order Partial Derivatives 49 7.7 Exercise 50 Topics 51 8.1 Binary Classification 52 8.2 The Confusion Matrix and ROC Curve 53 8.3 Indefinite Integrals 54 8.4 Definite Integrals 55 8.5 Numeric Integration with Python 56 8.6 Exercises 57 8.7 Finding the Area Under the ROC Curve 58 8.8 Resources for Further Study of Calculus ![]() ![]() ![]() |