Course Overview
- Gain theoretical knowledge regarding the different Machine Learning algorithms
- Learn the concepts of SVM and SVR in this Machine Learning Course
- Learn about supervised and unsupervised learning concepts and clustering
Who should attend this Machine Learning Training Course?
The Machine Learning Course is an intensive and comprehensive course designed to provide a deep dive into the fundamental concepts and applications of Machine Learning. The following are some professionals who can benefit greatly from this course:
- Data Scientists
- Data Analysts
- Software Engineers
- Business Analysts
- Operations Managers
- HR Professionals
- Project Managers
- Customer Service Managers
Prerequisites of the Machine Learning Training Course
Delegates must have a basic understanding of Python Programming and Statistics.
What’s included in this Machine Learning Training Course?
- World-Class Training Sessions from Experienced Instructors
- Machine Learning Certificate
- Digital Delegate Pack
Course Outline:
Module 1: Machine Learning – Introduction
- What is Machine Learning?
- Main Elements of Machine Learning
- Traditional Programming Vs Machine Learning
- Real Time Applications of Machine Learning
Module 2: Importance of Machine Learning and its Techniques
- Importance of Machine Learning
- Types of Machine Learning
- How Machine Learning Works?
Module 3: Machine Learning Mathematics
- What is Machine Learning Mathematics?
- Why Mathematics is Significant for Machine Learning?
Module 4: Data Pre-Processing
- What is Data Pre-Processing?
- Way to Handling Missing Values
Module 5: Supervised Learning
- Introduction to Supervised Learning
Module 6: Classification
- Introduction to Classification
- Types of Learners
- Support Vector Machines (SVM)
- How does SVM Work?
- Discriminant Analysis
- Naive Bayes
- Nearest Neighbour
Module 7: Regression
- Introduction to Regression
- Regression Models
- Linear Regression and GLM
- SVR
- Decision Tree
- Neural Networks
Module 8: Unsupervised Learning
- What is Unsupervised Learning?
- Difference Between Supervised and Unsupervised Learning
Module 9: Clustering
- Introduction to Clustering
- K-Means
- K-Medoids
- Fuzzy
- Hierarchal
- Gaussian Mixture
- Hidden Markov Model
Module 10: Deep Learning
- Introduction to Deep Learning
- Importance of Deep Learning
- How Deep Learning Works?
