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Course Details
Topic 1 Overview of Machine Learning
- Introduction to Machine Learning
- Pattern Recognition Problems Suitable for Machine Learning
- Supervised vs Unsupervised Learnings
- Types of Machine Learning
- Machine Learning Techniques
- R Packages for Machine Learning
Topic 2 Regression
- What is Regression
- Applications of Regression
- Least Square Error Minimization
- Data Pre-processing
- Bias vs Variance Trade-off
- Regression Methods with Regularization
Topic 3 Classification
- What is Classification
- Applications of Classification
- Classification Algorithms
- Confusion Matrix
- Classification Performance Evaluation
Topic 4 Clustering
- What is Clustering
- Applications of Clustering
- Distance Measure
- Clustering Algorithms
- Clustering Performance Evaluation
- Anomaly Detection Problem
Topic 5 Principal Component Analysis
- Principal Component Analysis (PCA) and Dimension Reduction
- Applications of PCA
- PCA Workflow
Topic 6 Neural Network
- What is Neural Network
- Activation Functions
- Deep Learning vs Machine Learning
- Classification Using Neural Network
Topic 7 Ensemble Methods
- Random Forest Ensemble
- Gradient Boost and XGBoost Ensemble
- Stacking Ensemble
Topic 8 Hyperparameter Tuning
- Exhaustive Grid
- Random Search
Course Info
Prerequisite:
This is an intermediate course. the following knowledge is assumed
Software Requirement
Pls download and install the following software prior to the class
HRDF Funding
Please refer to this video https://youtu.be/Kzpd-V1F9Xs
1- HRD Corp Grant Helper
How to submit grant applications for HRD Corp Claimable Courses
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Second, Click Application
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Insert MiCAS Application number
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Job Roles
- Data Scientists
- Data Analysts
- Marketeers
Trainers
Dr Azam: Dr Azam is an aerospace engineer with a passion for machine learning. He self-taught himself R statistical methods and has developed a machine learning course specifically for mechanical engineers; curating example case studies where traditional engineering analysis benefitted from machine learning techniques. Currently, he is involved in analyzing data from an oil platform as part of a large predictive maintenance package. He is also interested in mobile app development and has consulted a few businesses to modernize their point of sale system using tailor-made Android apps. He has supervised final year projects related to Android mobile apps and one of the projects has won a silver award for the best project overall.
Saranya Ravikumar: Saranya Ravikumar has a Master of Engineering in Computer Science and Engineering and worked as an Assistant Professor in a reputed Engineering College in India. She is a Dell EMC-certified Data Analyst. With a passion for teaching, she has more than 4 years of experience as an Assistant professor in Engineering Colleges. Also, she has more than 2 years of experience in leveraging technical concepts through effective lectures in order to make the listeners gain practical knowledge on the technical concepts of R, Python, and Data Analytics using R. She has trained more than 100 students in R Technical skills which has an outcome of some students be placed in a leading MNC as Junior Analyst. She has received the best project supervisor award for guiding the students in Technovision 2018 at a reputed Engineering College. Moreover, she has worked on many Big Data Projects in the fields of Plantation, Banking, and Security including Multivariate Regression, Time series Forecasting and Classification.
Customer Reviews (6)
- will recommend Review by Course Participant/Trainee
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Some of the methods needs to give examples and shows how. Its been calculated (Posted on 20/09/2023)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - might recommend Review by Course Participant/Trainee
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. (Posted on 25/02/2023)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - might recommend Review by Course Participant/Trainee
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. (Posted on 24/02/2023)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - might recommend Review by Course Participant/Trainee
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/ (Posted on 10/07/2021)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - might recommend Review by Course Participant/Trainee
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Can tell what is Machine Learning is use for and why we need to learn (Posted on 09/07/2021)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - will recommend Review by Course Participant/Trainee
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. (Posted on 06/03/2020)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
