Machine Learning Algorithms Complete Course
Master Core Machine Learning Algorithms with Real-World Examples
Updated on Jun, 2025
Language - English
IT and Software ,Other IT and Software,Python
Lectures -10
Duration -1.5 hours
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Course Description
Machine Learning Algorithms Complete Course:
This course will take you to the depths of Machine Learning with a complete focus on learning the most important algorithms in the field. This course is for beginners or those with some experience. You will learn supervised, unsupervised, and reinforcement learning with real-world datasets.You will study Linear Regression, Decision Trees, KNN, Naive Bayes, SVMs, Random Forests, K-Means, and more! You will understand how these algorithms work, how to develop them with your own code from scratch, and how to apply libraries like Scikit-learn. You will feel confident about your abilities, take a step towards algorithmic thinking, prepare to use ML techniques to solve real-world problems!
This course will take you to the depths of Machine Learning with a complete focus on learning the most important algorithms in the field. This course is for beginners or those with some experience. You will learn supervised, unsupervised, and reinforcement learning with real-world datasets.You will study Linear Regression, Decision Trees, KNN, Naive Bayes, SVMs, Random Forests, K-Means, and more! You will understand how these algorithms work, how to develop them with your own code from scratch, and how to apply libraries like Scikit-learn. You will feel confident about your abilities, take a step towards algorithmic thinking, prepare to use ML techniques to solve real-world problems!
Goals
Course Goals -- Understand how Machine Learning works
- Learn and implement popular machine learning algorithms, including Linear Regression, Logistic Regression, Decision Trees, KNN, Naive Bayes, SVM, etc.
- Work with real-life datasets to complete classification, regression, and clustering tasks.
- Preprocess and clean data with different python libraries (e.g.Pandas and Numpy).
- Visually display your data and model performance using Matplotlib and Seaborn.
- Evaluate your models with accuracy, precision, recall and more.
- Develop real world machine learning projects with Scikit-learn, and your own code
- Gain the confidence to pursue a career as a ML practitioner, data scientist, or in AI related roles.
Prerequisites
Course Prerequisites -- Basic knowledge of Python programming
- Basic understanding of math and statistics (high school level)
- No prior experience in machine learning required
- A computer with internet access and Jupyter/Google Colab setup
Curriculum
Check out the detailed breakdown of what’s inside the course
Machine learning Algorithms mastery course
10 Lectures
-
Introduction To Course
03:17
03:17
-
Class 1 : Linear Regression Algorithm Explanation
08:11
08:11
-
Class 2 : Logistic Regression Algorithm Explanation
05:24
05:24
-
Class 3 : Naive Bayes Algorithm Explanation
09:29
09:29
-
Class 4 : Support Vector Machine Algorithm Explanation
11:07
11:07
-
Class 5 : K means Clustering Algorithm Explanation
05:51
05:51
-
Class 6 : KNN Algorithm Explanation
07:24
07:24
-
Class 7 : Decision Tree Algorithm Explanation
08:29
08:29
-
Class 8 : Random Forest Algorithm Explanation
05:40
05:40
-
ML Project : Hate Speech Detection Using ML
31:37
31:37
Instructor Details
Arunnachalam Shanmugaraajan
Guiding Students to Excellence in Life
Hi, I'm Arunnachalam R S from India — a Computer Science graduate with a strong passion for Cybersecurity and emerging technologies. I’ve chosen cybersecurity as my professional domain and am deeply committed to staying ahead in this ever-evolving field.
As a tech educator, I enjoy sharing my knowledge about the latest technological advancements, security practices, and innovations in science and IT. My mission is to simplify complex concepts and help learners of all levels gain practical skills they can apply in real-world scenarios.
I’m excited to be part of the TutorialsPoint platform, where I can express my passion for technology, contribute to the global learning community, and empower others through quality education.
As a tech educator, I enjoy sharing my knowledge about the latest technological advancements, security practices, and innovations in science and IT. My mission is to simplify complex concepts and help learners of all levels gain practical skills they can apply in real-world scenarios.
I’m excited to be part of the TutorialsPoint platform, where I can express my passion for technology, contribute to the global learning community, and empower others through quality education.
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