Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. The capability of Artificial Intelligence systems to learn by extracting patterns from data is known as Machine Learning.
Machine learning Course Description
In this tutorial, we will learn about Machine Learning, Machine Learning benefits, and various Machine Learning applications.
Some machine learning methods are:-
- Linear Regression: Learn to implement linear regression and predict continuous data values
- Supervised Learning: Understand and implement algorithms like Naive Bayes and Logistic Regression
- Unsupervised Learning: Learn how to create segments based on similarities using K-Means and Hierarchical clustering
- Support Vector Machines: Learn how to classify data points using support vectors
- Decision Trees: Tree-based model that is simple and easy to use. Learn the fundamentals on how to implement them.
Features of Machine Learning
Let us look at some of the features given below in this Machine Learning tutorial.
- Machine Learning is computing-intensive and generally requires a large amount of training data.
- It involves repetitive training to improve the learning and decision making of algorithms.
- As more data gets added, Machine Learning training can be automated for learning new data patterns and adapting its algorithm.
Machine Learning Benefits
Let us look at some of the benefits in this Machine Learning Course.
- Powerful Processing
- Better Decision Making & Prediction
- Quicker Processing
- Affordable Data Management
- Analyzing Complex Big Data
Machine Learning Techniques
Given below are some techniques in this Machine Learning tutorial.
- Trend analysis
- Anomaly detection
- Decision making
Applications of Machine Learning
Some of the applications of Machine learning mentioned below.
- Image Processing
- Data Mining
- Video Games
- Text Analysis
Mapping Minds Team
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