Size: 2.12 GB
Applications: decrypting ciphers, spam detection, sentiment analysis, article spinners, and latent semantic analysis.
What you’ll learn
- Write your own spam detection code in Python
- Write your own sentiment analysis code in Python
- Perform latent semantic analysis or latent semantic indexing in Python
- Have an idea of how to write your own article spinner in Python
Requirements
- Install Python, it’s free!
- You should be at least somewhat comfortable writing Python code
- Install numerical libraries for Python such as Numpy, Scipy, Scikit-learn, Matplotlib, and BeautifulSoup
- Take my free Numpy prerequisites course (it’s FREE, no excuses!) to learn about Numpy, Matplotlib, Pandas, and Scikit-Learn, as well as Machine Learning basics
- Optional: If you want to understand the math parts, linear algebra and probability are helpful
Description
In this course you will build MULTIPLE practical systems using natural language processing, or NLP – the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn’t contain any hard math – just straight up coding in Python. All the materials for this course are FREE.- Python coding: if/else, loops, lists, dicts, sets
- Take my free Numpy prerequisites course (it’s FREE, no excuses!) to learn about Numpy, Matplotlib, Pandas, and Scikit-Learn, as well as Machine Learning basics
- Optional: If you want to understand the math parts, linear algebra and probability are helpful
- Watch it at 2x.
- Take handwritten notes. This will drastically increase your ability to retain the information.
- Ask lots of questions on the discussion board. The more the better!
- Realize that most exercises will take you days or weeks to complete.
- Write code yourself, don’t just sit there and look at my code.
- Check out the lecture “What order should I take your courses in?” (available in the Appendix of any of my courses, including the free Numpy course)
Who this course is for:
- Students who are comfortable writing Python code, using loops, lists, dictionaries, etc.
- Students who want to learn more about machine learning but don’t want to do a lot of math
- Professionals who are interested in applying machine learning and NLP to practical problems like spam detection, Internet marketing, and sentiment analysis
- This course is NOT for those who find the tasks and methods listed in the curriculum too basic.
- This course is NOT for those who don’t already have a basic understanding of machine learning and Python coding (but you can learn these from my FREE Numpy course).
- This course is NOT for those who don’t know (given the section titles) what the purpose of each task is. E.g. if you don’t know what “spam detection” might be useful for, you are too far behind to take this course.
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