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Machine Learning from Scratch

Track :

Programming

Lessons no : 15

For Free Certificate After Complete The Course

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What will you learn in this course?
  • Develop foundational machine learning algorithms like linear regression and decision trees for practical data analysis tasks
  • Implement data preprocessing, feature engineering, and model evaluation techniques to improve prediction accuracy
  • Apply supervised and unsupervised learning methods to real-world datasets for classification and clustering projects
  • Utilize Python libraries such as NumPy, pandas, and scikit-learn to build and test machine learning models from scratch
  • Analyze model performance using metrics like accuracy, precision, recall, and F1 score for informed decision-making
  • Design and optimize machine learning workflows to handle large datasets efficiently and effectively
  • Troubleshoot common issues in machine learning models, including overfitting, underfitting, and bias-variance tradeoff
  • Integrate machine learning models into applications and systems for predictive analytics and automation solutions

How to Get The Certificate

  • You must have an account Register
  • Watch All Lessons
  • Watch at least 50% of Lesson Duration
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  • The Certificate is free !
Lessons | 15

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NITIN KUMAWAT 

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2025-03-28

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Machine learning is the process of using computers to detect patterns in massive datasets and then make predictions based on what the computer learns from those .