Machine Learning Fundamentals

4h 5m 9s
English
Paid

Course description

Advance your career in machine learning with confidence. Master the key ML fundamentals that are in demand by employers and acquire the skills necessary to solve real-world problems. Start building a successful future in the tech field today!

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#1: Introduction

All Course Lessons (21)

#Lesson TitleDurationAccess
1
Introduction Demo
06:55
2
1. Machine Learning Basics
15:27
3
2. Bias-Variance Trade-off
07:11
4
3. Overfitting Regularization
15:31
5
4.1 Linear Regression - Causal Analysis (Part 1)
14:51
6
4.2 Linear Regression - (Part 2)
24:25
7
5. Logistic Regression & Maximum Likelihood Estimation (MLE)
15:09
8
6. Linear Discriminant Analysis (LDA)
11:15
9
7. K-Nearest Neighbors (KNN)
11:52
10
8. Decision Trees
16:45
11
9. Bagging
07:54
12
10. Random Forest
08:11
13
11. (Boosting Part 1) Introduction
08:01
14
12. Boosting (Part 2) - AdaBoost
10:00
15
13. Boosting (Part 3) - Gradient Boosting Model (GBM)
10:53
16
14. Boosting (Part 4) - XGBoost
08:08
17
15. Clustering (Part 1) - K-Means & Elbow Method
17:43
18
16. Clustering (Part 2) - Hierarchical Clustering
10:49
19
17. Clustering (Part 3) - DBScan
07:45
20
18. Dimensionality Reduction (Part 1) - Feature Selection
07:32
21
19. Dimensionality Reduction (Part 2) - Principal Component Analysis
08:52

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