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Introduction to Machine Learning
Introduction to Machine Learning
Curriculum
4 Sections
27 Lessons
Lifetime
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1.Mathematics for Machine Learning
14
1.1
Why Mathematics for Machine Learning?
1.2
1.1 Linear Algebra
1.3
1.1.1 Vectors
1.4
1.1.2 Vector Operators
1.5
Quiz – Vectors
5 Questions
1.6
1.2.1 Matrices
1.7
1.2.2 Matrix Operators
1.8
Quiz – Matrices
7 Questions
1.9
1.2 Statistics
1.10
1.2.1 Descriptive Statistics
1.11
Quiz – Descriptive Statistics
5 Questions
1.12
1.3 Probabilities
1.13
1.3.1 Basic Probability Rules
1.14
Quiz – Mathematics for ML
5 Questions
2. Process of Machine Learning
6
2.1
2.1 Machine Learning – Introduction
2.2
2.2 Deep Learning – Introduction
2.3
2.3 Generative AI – Introduction
2.4
2.4 Generative Learning – Introduction
2.5
2.5 Generative Adversarial Network (GAN) – Introduction
2.6
Quiz – Process of ML
5 Questions
3. Types of Machine Learning
5
3.1
3.0 Overfitting, Underfitting, Bias-Variance Trade-Off
3.2
3.1 What is Supervised Learning?
3.3
3.2 What is Unsupervised Learning?
3.4
3.3 What is Reinforcement Learning?
3.5
Quiz – Types of ML
0 Questions
4. Machine Learning Workflow
9
4.1
4.1 Data Collection
4.2
4.2 Data Preprocessing
4.3
4.3 Feature Engineering
4.4
4.4 Model Selection
4.5
4.5 Training the Model
4.6
4.6 Model Validation & Evaluation
4.7
4.7 Model Tuning
4.8
4.8 Model Deployment
4.9
Quiz – ML Workflow
0 Questions
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