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Machine Learning Training
Data Analytics & AIUnlock the Power of AI: Master Machine Learning for Cutting-Edge Applications and Innovation.
See Related CourseWhat you'll learn
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Gain a foundational understanding of what machine learning is, how it differs from traditional programming, and its real-time applications across various industries.
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Explore the importance of machine learning, including an overview of different types, such as supervised, unsupervised, and reinforcement learning, and how these techniques function.
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Delve into the essential mathematics behind machine learning, emphasising why a strong mathematical foundation is crucial for effective model building and analysis.
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Learn about data pre-processing techniques, including methods for handling missing data, which is a critical step in preparing data for machine learning algorithms.
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Understand the principles of supervised learning and explore various models and algorithms used to make predictions based on labeled data.
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Study classification techniques within machine learning, covering algorithms like Support Vector Machines (SVM), Naive Bayes, and Nearest Neighbour, and their applications.
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Examine regression techniques, understanding models like linear regression, Generalised Linear Models (GLM), and Support Vector Regression (SVR), among others.
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Contrast supervised and unsupervised learning, focusing on the latter's methodologies and applications, particularly in pattern detection and inference without labeled data.
This course includes
tv8h On-demand Video
Skills you will gain
- Fundamental Understanding
- Technical Proficiency
- Mathematical Foundation
- Data Handling
- Model Development
- Advanced Techniques
Prerequisites
- Understanding of basic mathematical concepts, including algebra, calculus, and statistics.
- Ability to analyse and interpret data effectively.
- Prior experience with data handling and pre-processing techniques.
- Strong problem-solving skills to tackle complex machine learning challenges.
- A keen interest in artificial intelligence and machine learning technologies.
10 sections
25 Activities
10
15
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Machine Learning - Introduction
11m 38s
Brief Knowledge
0m 0s
Importance of Machine Learning and its Techniques
9m 5s
Fill in the Blanks
0m 0s
Find the Words
0m 0s
Machine Learning Mathematics
2m 24s
Flash Cards
0m 0s
Data Pre-Processing
27m 49s
Drag the Words
0m 0s
Quiz
0m 0s
Supervised Learning
8m 43s
True & False
0m 0s
Classification
36m 3s
Check your Knowledge
0m 0s
Single Choice Set
0m 0s
Regression
25m 17s
Multiple Choice Questions
0m 0s
Unsupervised Learning
5m 3s
Presentation
0m 0s
Mark the Words
0m 0s
Clustering
30m 59s
Dialog Cards
0m 0s
Deep Learning
9m 0s
Complex Fill in the Blanks
0m 0s
Interactive Book
0m 0s
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