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  • Book Overview & Buying Building Machine Learning Systems with Python
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Building Machine Learning Systems with Python

Building Machine Learning Systems with Python - Third Edition

By : Pedro Coelho, Willi Richert , Brucher
1.7 (3)
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Building Machine Learning Systems with Python

Building Machine Learning Systems with Python

1.7 (3)
By: Pedro Coelho, Willi Richert , Brucher

Overview of this book

Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI). With this guide’s hands-on approach, you’ll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You’ll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you’ll understand how to use Python’s scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance. By the end of this book, you’ll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.
Table of Contents (17 chapters)
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1
Getting Started with Python Machine Learning

Classification I – Detecting Poor Answers

A continuous challenge for owners of Q&A sites is to maintain a decent level of quality in the posted content. Sites such as StackOverflow make considerable effort to encourage users with diverse possibilities to score content, and offer badges and bonus points to spend more energy on carving out the question or crafting a possible answer.

One particularly successful incentive is the ability for the asker to flag one answer to their question as the accepted answer (there are incentives for the asker to flag answers as such). This will result in a higher score for the author of the flagged answer.

Would it not be very useful for the user to immediately see how good their answer is while typing it in? That means the website would continuously evaluate the user's work-in-progress answer and provide feedback as to whether the...

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