Master Machine Learning: From Basics to Advanced Models
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3:38:04
1 - Introduction to Machine Learning.mp4
09:17
2 - Types of Machine Learning.mp4
11:18
3 - Polynomial Curve Fitting.mp4
08:43
4 - Probability.mp4
10:42
5 - Total Probability Bayes Rule and Conditional Independence.mp4
08:11
6 - Random Variables and Probability Distribution.mp4
07:42
7 - Expectation Variance Covariance and Quantiles.mp4
09:28
8 - Maximum Likelihood Estimation.mp4
12:14
9 - Least Squares Method.mp4
07:02
10 - Robust Regression.mp4
06:43
11 - Ridge Regression.mp4
09:37
12 - Bayesian Linear Regression.mp4
06:32
13 - Linear models for classificationDiscriminant Functions.mp4
12:44
14 - Probabilistic Discriminative and Generative Models.mp4
07:16
15 - Logistic Regression.mp4
05:30
16 - Bayesian Logistic Regression.mp4
03:50
17 - Kernel Functions.mp4
13:31
18 - Kernel Trick.mp4
04:45
19 - Support Vector Machine.mp4
11:23
20 - Kmeans clustering.mp4
10:08
21 - Mixtures of Gaussians.mp4
10:31
22 - EM for Gaussian Mixture Models.mp4
09:43
23 - PCA Choosing the number of latent dimensions.mp4
08:57
24 - Hierarchial clustering.mp4
12:17
More details
Course Overview
This comprehensive course takes you from fundamental machine learning concepts to advanced techniques, covering supervised and unsupervised learning, regression, classification, and time-series prediction. Gain hands-on experience with real-world applications.
What You'll Learn
- Apply linear models for regression and classification
- Develop clustering models using K-means and Gaussian mixtures
- Build ensemble models and predict time-series data
Who This Is For
- Students entering the field of data science
- Data scientists looking to enhance their predictive modeling skills
- Engineers solving data-driven problems
Key Benefits
- Master both theoretical foundations and practical applications
- Learn from basic probability to advanced Bayesian methods
- Gain skills applicable to real-world data challenges
Curriculum Highlights
- Introduction to Machine Learning Fundamentals
- Linear Models for Regression and Classification
- Mixture Models and Clustering Techniques
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Category
- language english
- Training sessions 24
- duration 3:38:04
- Release Date 2025/06/02
