Beginner
65 Lessons
14h
Certificate of Completion
Takeaway Skills
An understanding of the fundamental machine learning algorithms
Proficiency in strong problem-solving skills through hands-on projects
Working knowledge of applying machine learning algorithms to real-world datasets, addressing classification, regression, clustering, and dimensionality reduction tasks
Hands-on experience assessing and comparing the performance of machine learning models
Course Overview
This course focuses on core concepts, algorithms, and machine learning techniques. It explores the fundamentals, implements algorithms from scratch, and compares the results with scikit-learn, the Python machine learning library. This course contains examples, theoretical knowledge, and codes for various ML algorithms. You’ll start by learning the essentials of machine learning and its applications. Then, you’ll learn about supervised learning, clustering, and constructing a bag of visual words project, fo...
Course Content
Course Overview
Supervised Learning
Clustering
Project: Bag of Visual Words
Project
Generalized Linear Regression
Face Recognition Using Kernel Linear Discriminant
Project
Support Vector Machine
Logistic Regression
8 Lessons
Ensemble Learning
8 Lessons
Early Stage Diabetes Prediction Using Ensemble Learning
Project
Decoding Dimensions: PCA and Autoencoders
5 Lessons
Image Reconstruction Using PCA
Project
Image Colorization using Autoencoders
Project
Colorful Face Generation with VAEs
Project
Appendix
6 Lessons
Wrapping Up
1 Lesson
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