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Machine Learning For Beginners Using Python

Track :

Programming

Lessons no : 23

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What will you learn in this course?
  • Develop Python programming skills for machine learning applications using libraries like scikit-learn and pandas
  • Implement data preprocessing techniques for machine learning models, including cleaning, normalization, and feature engineering
  • Build and evaluate machine learning models such as regression, classification, and clustering algorithms in Python
  • Utilize Jupyter Notebook and Anaconda for effective data analysis, visualization, and model development workflows
  • Apply data visualization tools to interpret machine learning results and communicate insights clearly
  • Understand fundamental machine learning concepts including supervised, unsupervised, and reinforcement learning techniques
  • Optimize machine learning models through hyperparameter tuning and cross-validation methods
  • Identify and address common challenges in machine learning projects, such as overfitting and bias-variance tradeoff
  • Integrate Python-based machine learning models into real-world data science projects and applications
  • Develop problem-solving skills for deploying machine learning solutions in diverse industry scenarios

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Lessons | 23


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Md Shahid Afridi

Wonderful to learning journey 2024-09-07

Kumar Saurabh

the course was well designed learned a lot about using python libraries for machine learning. 2023-10-11

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Spend a few months learning Python code at the same time as different machine learning concepts. You'll need them both. Whilst learning Python code, practice using data science tools such as Jupyter and Anaconda. Spend a few hours tinkering with them .