AI & ML Algorithms and their Practical Applications

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最近下载：2024-10-04
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文档列表

Lesson 6 Deep Learning/004. 6.3 Convolutional Neural Networks (CNN) for Image Recognition.mp4 98.9 MB
Lesson 2 Unsupervised Learning/003. 2.2 How K-means Works, Advantages and Limitations.mp4 76.9 MB
Lesson 6 Deep Learning/002. 6.1 Why is this Learning Deep .mp4 76.8 MB
Lesson 4 Random Forests/003. 4.2 Build Your First Tree.mp4 54.9 MB
Lesson 6 Deep Learning/003. 6.2 Artificial Neural Networks (ANN) step-by-step.mp4 52.7 MB
Lesson 7 An Introduction to Large Language Models/003. 7.2 Word Embedding.mp4 42.7 MB
Lesson 7 An Introduction to Large Language Models/004. 7.3 Transformers.mp4 40.6 MB
Lesson 2 Unsupervised Learning/005. 2.4 DBSCAN for Complex Shapes.mp4 33.3 MB
Lesson 5 Reinforcement Learning/003. 5.2 Understanding Reinforcement Learning Components and Framework.mp4 32.0 MB
Lesson 7 An Introduction to Large Language Models/005. 7.4 Advanced Topics.mp4 31.9 MB
Lesson 2 Unsupervised Learning/004. 2.3 Hierarchical Clustering.mp4 31.2 MB
Introduction/001. AI and ML Algorithm Foundations Introduction.mp4 31.0 MB
Lesson 7 An Introduction to Large Language Models/002. 7.1 How did Large Language Models (LLMs) Develop.mp4 30.7 MB
Lesson 5 Reinforcement Learning/005. 5.4 Q-Learning.mp4 30.2 MB
Lesson 1 An Introduction to the World of Artificial Intelligence and Machine Learning/003. 1.2 AI and ML Definitions.mp4 29.5 MB
Lesson 2 Unsupervised Learning/002. 2.1 Clustering Principles.mp4 26.9 MB
Lesson 3 Supervised Learning/003. 3.2 Linear Regression Fitting a Curve with Training Data.mp4 26.0 MB
Lesson 3 Supervised Learning/008. 3.7 Classification 2 - Support Vector Machines (SVM).mp4 25.5 MB
Lesson 4 Random Forests/004. 4.3 Build a Full Forest.mp4 22.7 MB
Lesson 3 Supervised Learning/005. 3.4 Gradient Descent.mp4 21.4 MB
Lesson 3 Supervised Learning/002. 3.1 Predictive Functions.mp4 16.2 MB
Lesson 3 Supervised Learning/007. 3.6 Classification 1 Logistical Regression.mp4 15.8 MB
Lesson 1 An Introduction to the World of Artificial Intelligence and Machine Learning/002. 1.1 A Brief History of AI and ML.mp4 15.4 MB
Lesson 3 Supervised Learning/006. 3.5 The Machine Learning Workflow.mp4 14.1 MB
Lesson 4 Random Forests/002. 4.1 Why Use Trees.mp4 14.0 MB
Lesson 5 Reinforcement Learning/002. 5.1 Why Reinforcement Learning.mp4 13.8 MB
Lesson 1 An Introduction to the World of Artificial Intelligence and Machine Learning/004. 1.3 Discriminative vs. Generative AI.mp4 12.7 MB
Summary/001. AI and ML Algorithm Foundations Summary.mp4 10.9 MB
Lesson 5 Reinforcement Learning/004. 5.3 The Bellman Value Equation.mp4 10.8 MB
Lesson 2 Unsupervised Learning/001. Learning objectives.mp4 8.6 MB
Lesson 4 Random Forests/001. Learning objectives.mp4 7.3 MB
Lesson 6 Deep Learning/001. Learning objectives.mp4 7.0 MB
Lesson 5 Reinforcement Learning/001. Learning objectives.mp4 5.4 MB
Lesson 7 An Introduction to Large Language Models/001. Learning objectives.mp4 4.7 MB
Lesson 3 Supervised Learning/001. Learning objectives.mp4 4.3 MB
Lesson 3 Supervised Learning/004. 3.3 The Cost Function.mp4 4.2 MB
Lesson 1 An Introduction to the World of Artificial Intelligence and Machine Learning/001. Learning objectives.mp4 3.0 MB

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