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Byte-Sized-Chunks: Twitter Sentiment Analysis (in Python)

All this is in the run up to a serious project to perform Twitter Sentiment Analysis. We'll spend some time on Regular Expressions which are pretty handy to know as we'll see in our code-along.
Byte-Sized-Chunks: Twitter Sentiment Analysis (in Python)
  • 1299
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: Online Course
: English
: Loonycorn
Displaying 1-4 of 4 result(s).

About Course

  •  

    Sentiment Analysis (or) Opinion Mining is a field of NLP that deals with extracting subjective information (positive/negative, like/dislike, emotions).

    • Learn why it's useful and how to approach the problem: Both Rule-Based and ML-Based approaches.
    • The details are really important - training data and feature extraction are critical. Sentiment Lexicons provide us with lists of words in different sentiment categories that we can use for building our feature set.
    • All this is in the run up to a serious project to perform Twitter Sentiment Analysis. We'll spend some time on Regular Expressions which are pretty handy to know as we'll see in our code-along.

    Sentiment Analysis:

    • Why it's useful,
    • Approaches to solving - Rule-Based , ML-Based
    • Training & Feature Extraction
    • Sentiment Lexicons
    • Regular Expressions
    • Twitter API
    • Sentiment Analysis of Tweets with Python

Curriculam

What you will get from this course?

    • Design and Implement a sentiment analysis measurement system in Python
    • Grasp the theory underlying sentiment analysis, and its relation to binary classification
    • Identify use-cases for sentiment analysis

Who should buy this course?

  •  

    • Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
    •  Engineers who want to understand or learn machine learning and apply it to problems they are solving
    • Tech executives and investors who are interested in big data, machine learning or natural language processing
    • Product managers who want to have intelligent conversations with data scientists and engineers about machine learning

    What are the requirements?

    • No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to perform the coding exercise and understand the provided source code
 
 
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Loonycorn is us, Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh. Between the four of us, we have studied at Stanford, IIM Ahmedabad, the IITs and have spent years (decades, actually) working in tech, in the Bay Area, New York, Singapore and Bangalore.

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