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

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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.