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.
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.
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

Last updated 10/2018