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What Will You Learn?
About This Course
The "Machine Learning" course provides an in-depth exploration of the foundational techniques and applications in the field of machine learning. Students will gain practical experience with algorithms for supervised and unsupervised learning, model evaluation, and optimization. The course combines theoretical concepts with hands-on projects using popular tools and frameworks, enabling participants to build and deploy machine learning models for real-world problems. By integrating lectures, coding exercises, and case studies, this course aims to equip learners with the skills necessary to leverage machine learning in diverse domains.
Requirements
Digital Moran is a community-based talent incubator and grassroots tech movement. It is dedicated to empowering rural and underprivileged youth in Kenya by providing free, accessible digital skills training.
The organization's mission is to challenge the belief that success can only be found in the city. It provides a direct path from learning to earning by equipping youth with high-value digital skills in areas like web design, graphic design, digital marketing, and AI.
Digital Moran operates on a "tools, not handouts" philosophy. It consists of two main parts: the Digital Moran Academy, a free online learning hub with over 50 courses, and the Digital Moran Agency, an exclusive marketplace that ...
Curriculum Overview
This course includes 1 modules, 43 lessons, and 0 hours of materials.
Machine Learning
43 Parts
Machine Learning Specialization
Free
Volume
-
Intro Video
Free
Volume
-
Applications of Machine Learning
Free
Volume
-
What is Machine Learning
Free
Volume
-
Supervised Learning Part 1
Free
Volume
-
Supervised Learning Part 2
Free
Volume
-
Unsupervised Learning Part 1
Free
Volume
-
Unsupervised Learning Part 2
Free
Volume
-
Jupyter Notebooks
Free
Volume
-
Linear Regression Model Part 1
Free
Volume
-
Linear Regression Model Part 2
Free
Volume
-
Cost Function
Free
Volume
-
Cost Function Intuition
Free
Volume
-
Visualizing The Cost Function
Free
Volume
-
Visualization Examples
Free
Volume
-
Gradient Descent
Free
Volume
-
Implementing Gradient Descent
Free
Volume
-
Gradient Descent Intuition
Free
Volume
-
Learning Rate
Free
Volume
-
Gradient Descent for Linear Regression
Free
Volume
-
Running Gradient Descent
Free
Volume
-
Multiple Features
Free
Volume
-
Vectorization Part 1
Free
Volume
-
Vectorization Part 2
Free
Volume
-
Gradient Descent for Multiple Linear Regression
Free
Volume
-
Feature Scaling Part 1
Free
Volume
-
Feature Scaling Part 2
Free
Volume
-
Checking Gradient Descent for Convergence
Free
Volume
-
Choosing The Learning Rate
Free
Volume
-
Feature Engineering
Free
Volume
-
Polynomial Regression
Free
Volume
-
Motivation
Free
Volume
-
Logistic Regression
Free
Volume
-
Decision Boundary
Free
Volume
-
Cost Function for Logistic Regression
Free
Volume
-
Simplified Cost Function
Free
Volume
-
Gradient Descent Implementation
Free
Volume
-
The Problem of Overfitting
Free
Volume
-
Addressing Overfitting
Free
Volume
-
Cost Function with Regularization
Free
Volume
-
Regularized Linear Regression
Free
Volume
-
Regularized Logistic Regression
Free
Volume
-
Outro Video
Free
Volume
-
Certificates
1 Parts
Course Certificate
Course Certificate
If you pass all the lessons in this course, you will receive this certificate.
Type
Course Certificate
0
0 Reviews
Content Quality (0)
Instructor Skills (0)
Value for Money (0)
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Course Specifications
Sections
1
Lessons
43
Capacity
Unlimited
Duration
5:03 Hours
Students
40
Created Date
3 Aug 2024
Updated Date
23 Feb 2025
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Machine Learning
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