From the course: Advanced NLP with Python for Machine Learning

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Build a model on TF-IDF vectors

Build a model on TF-IDF vectors - Python Tutorial

From the course: Advanced NLP with Python for Machine Learning

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Build a model on TF-IDF vectors

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- [Instructor] Whenever you're building a machine learning model, it's important to start with some kind of baseline, a model that's not too complicated, they will serve as a benchmark to see if you're more complex models are actually improving the performance. We should always try and stick to outcomes razor. We should prefer the simpler model, unless the added complexity is worth the improvement in performance. In this lesson, we're going to fit our baseline model, which is a RandomForestModel built on top of TF-IDF vectors. This baseline will give us a starting point to understand how much there's to gain with more complex methods like Word2vec, Doc2vec, and recurrent neural networks. We already fit a basic model on TF-IDF vectors in the review chapter. So I'm going to go through this quickly. Feel free to revisit the review chapter, if you want more detail on any of the steps here. Let's start by reading in our…

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