![Advanced NLP with Python for Machine Learning [Repost]](https://pixhost.icu/avaxhome/5f/1b/00a71b5f_medium.jpg)
Advanced NLP with Python for Machine Learning [Repost]
![Advanced NLP with Python for Machine Learning [Repost]](https://pixhost.icu/avaxhome/5f/1b/00a71b5f.jpg)
Advanced NLP with Python for Machine Learning
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 9m | 323 MB
Instructor: Derek Jedamski
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 9m | 323 MB
Instructor: Derek Jedamski
An incredible amount of unstructured text data is generated every day by social media, web pages, and a variety of other sources. But without the ability to tame and harness that data, you'll be unable to glean any value from it. In this course, learn how to translate messy text data into powerful insights using Python.
Instructor Derek Jedamski begins with a quick review of foundational NLP concepts, including how to clean text data and build a model on top of vectorized text. He then jumps into more complex topics such as word2vec, doc2vec, and recurrent neural networks. To wrap up the course, he lends these concepts a real-world context by applying them to a machine learning problem.
Learning objectives
- Explain the importance of natural language processing (NLP).
- Analyze how to clean text data.
- Interpret the importance of building a model on top of vectorized text.
- Explain the importance of word2vec.
- Apply techniques to prepare document vectors for modeling.
- Examine recurrent neural networks (RNNs).
- Evaluate methods using key performance metrics.
![Advanced NLP with Python for Machine Learning [Repost]](https://pixhost.icu/avaxhome/60/1b/00a71b60_medium.jpg)
Advanced NLP with Python for Machine Learning [Repost]
![Advanced NLP with Python for Machine Learning [Repost]](https://pixhost.icu/avaxhome/60/1b/00a71b60.jpg)