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AI Machine Learning

Track :

Programming

Lessons no : 20

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What will you learn in this course?
  • Develop practical skills in designing and implementing machine learning algorithms for real-world AI applications
  • Apply data preprocessing, feature engineering, and model training techniques to improve machine learning performance
  • Evaluate and optimize machine learning models using metrics like accuracy, precision, recall, and F1 score
  • Utilize popular machine learning frameworks and tools such as TensorFlow, scikit-learn, and Keras
  • Identify appropriate machine learning methods for different AI problems, including supervised, unsupervised, and reinforcement learning
  • Implement ethical AI practices and address bias, fairness, and transparency in machine learning models
  • Troubleshoot common issues in machine learning workflows, including overfitting, underfitting, and data imbalance
  • Integrate machine learning models into AI systems for automation, prediction, and decision-making processes

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  • Watch All Lessons
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Lessons | 20


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Ahilya Adsule

Excellent
2025-10-22

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very good
2025-10-08

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Nice
2025-10-06

Vedu Mistry

excellent
2025-10-04

Chaudhary Manjula (Mi)

very nice course🤩
2025-09-26

Anjal Rami

Nice
2025-09-25

SAHIL PATEL

AMAZING
2025-09-24

yogesh singh rawat

nice course
2025-05-27

Hemant Charoskar

It's very useful to college students.
2023-08-23

Amadi Emmanuel

Awesome learning on this great platform I recommend for both starters and professionala
2023-08-18

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l thought it was nice
2023-08-13

Mutasim

Thank you very much
2022-04-25

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Oftentimes, the terms machine learning and artificial intelligence (AI) are used interchangeably; however, they are not the same. AI is basically the umbrella concept, and machine learning is a subset of artificial intelligence.