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Python Machine Learning: From Techniques to Troubleshooting

Python Machine Learning: From Techniques to Troubleshooting

Python Machine Learning: From Techniques to Troubleshooting
Python Machine Learning: From Techniques to Troubleshooting, Use Machine Learning to make your Python apps smarter & build efficient, progressive models to tackle real-world data
Created by Packt Publishing
English
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What you'll learn
  • Perform regression in a supervised learning setting, so that you can predict numbers, prices, and conversion rates.
  • Perform classification in a supervised-learning setting, teaching the model to distinguish between different plants, discussion topics, and objects.
  • Read, explore, clean, and prepare your data using Pandas, the most popular library for analyzing data tables.
  • Use the Scikit-Learn library to deploy ready-built models, train them, and see results in just a few lines of code.
  • Eliminate common data wrangling problems in Pandas and scikit-learn.
  • Troubleshoot advanced models such as Random Forests and SVMs.
  • Perform common natural language processing featuring engineering tasks.
  • Requirements
  • Familiarity with the Python data science ecosystem: Pandas, scikit-learn, Matplotlib is assumed.

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