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Machine Learning basics

Track :

Programming

Lessons no : 11

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What will you learn in this course?
  • Understand core machine learning concepts including algorithms, models, and training processes for practical implementation
  • Apply supervised and unsupervised learning techniques to real-world data analysis and problem-solving
  • Evaluate machine learning models using accuracy, precision, recall, and other performance metrics for optimal results
  • Implement data preprocessing, feature engineering, and model tuning to enhance machine learning outcomes
  • Identify suitable machine learning algorithms for specific tasks such as classification, regression, and clustering
  • Utilize popular machine learning tools and libraries like scikit-learn, TensorFlow, and Keras for project development
  • Troubleshoot common issues in machine learning workflows, including overfitting, underfitting, and data imbalance
  • Develop foundational skills to pursue advanced topics in deep learning, reinforcement learning, and AI integration

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  • You must have an account Register
  • Watch All Lessons
  • Watch at least 50% of Lesson Duration
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Lessons | 11


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Thuwaraha Antonyraj 

Useful
2025-09-26

Rashi 

it is very usefull and good
2025-05-20

Feven Temesgen 

nice!
2025-01-13

SARA MOSHE WELDEHANA 

keep it up
2025-01-13

Abenezer Zerihun 

Good
2025-01-11

Burka 

The is very beneficial
2025-01-10

MUAZ Ahmed 

Best course in machine learning
2025-01-06

Lidiya Tsegaye 

nice
2025-01-04

Ponaganti Meghana 

Nice
2024-12-16

Pradnya kendole 

nice
2024-11-24

Danat 

i enjoyed it
2023-12-29

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Machine learning is an application of AI that enables systems to learn and improve from experience without being explicitly programmed .