Mathematical and Statistics Foundations for Machine Learning
Mathematical and Statistics Foundations for Machine Learning
Updated on Apr, 2024
Language - English
Lectures -55
Duration -7.5 hours
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Course Description
Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.
This training is an introduction to the concept of machine learning and its application using Python.
Target Customers:
- Anyone who wants to learn about data and analytics
- Data Engineers
- Analysts
- Architects
- Software Engineers
- IT operations
- Technical managers
Prerequisites
What are the prerequisites for this course?
- No prior knowledge of machine learning required
- Basic knowledge of the R tool
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
1 Lectures
-
Introduction to Machine Learning with Python
03:44
03:44
Importing
7 Lectures
Basics of Statistics Sampling
5 Lectures
Basics of Statistics Data types and Visualization
2 Lectures
Basics of Statistics Probability
6 Lectures
Basics of Statistics Random Variables
3 Lectures
Basics of Statistics Distributions
4 Lectures
Matrix Algebra
4 Lectures
Hypothesis Testing
10 Lectures
Hypothesis Tests-Types
11 Lectures
Regression
2 Lectures
Instructor Details
Corporate Bridge Consultancy Private Limited
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