Byte-Sized-Chunks: Twitter Sentiment Analysis (in Python)
Byte-Sized-Chunks: Twitter Sentiment Analysis (in Python), available at $34.99, has an average rating of 4.3, with 14 lectures, based on 96 reviews, and has 2829 subscribers.
You will learn about 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 This course is ideal for individuals who are Nope! Please don't enroll for this class if you have already enrolled for our 21-hour course 'From 0 to 1: Machine Learning and NLP in Python' or Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning or Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving or Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing or Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning It is particularly useful for Nope! Please don't enroll for this class if you have already enrolled for our 21-hour course 'From 0 to 1: Machine Learning and NLP in Python' or Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning or Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving or Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing or Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning.
Enroll now: Byte-Sized-Chunks: Twitter Sentiment Analysis (in Python)
Summary
Title: Byte-Sized-Chunks: Twitter Sentiment Analysis (in Python)
Price: $34.99
Average Rating: 4.3
Number of Lectures: 14
Number of Published Lectures: 14
Number of Curriculum Items: 14
Number of Published Curriculum Objects: 14
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
- 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 Attend
- Nope! Please don't enroll for this class if you have already enrolled for our 21-hour course 'From 0 to 1: Machine Learning and NLP in Python'
- Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
- Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving
- Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing
- Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
Target Audiences
- Nope! Please don't enroll for this class if you have already enrolled for our 21-hour course 'From 0 to 1: Machine Learning and NLP in Python'
- Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
- Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving
- Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing
- Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
Note: This course is a subset of our 20+ hour course ‘From 0 to 1: Machine Learning & Natural Language Processing’ so please don’t sign up for both:-)
Sentiment Analysis (or) Opinion Miningis 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
Course Curriculum
Chapter 1: What Are You Feeling Like?
Lecture 1: You, This Course, and Us!
Lecture 2: A Sneak Peek at what's coming up
Lecture 3: Sentiment Analysis – What's all the fuss about?
Lecture 4: ML Solutions for Sentiment Analysis – the devil is in the details
Lecture 5: Sentiment Lexicons ( with an introduction to WordNet and SentiWordNet)
Lecture 6: Installing Python – Anaconda and Pip
Lecture 7: Back to Basics : Numpy in Python
Lecture 8: Back to Basics : Numpy and Scipy in Python
Lecture 9: Regular Expressions
Lecture 10: Regular Expressions in Python
Lecture 11: Put it to work : Twitter Sentiment Analysis
Lecture 12: Twitter Sentiment Analysis – Work the API
Lecture 13: Twitter Sentiment Analysis – Regular Expressions for Preprocessing
Lecture 14: Twitter Sentiment Analysis – Naive Bayes, SVM and Sentiwordnet
Instructors
-
Loony Corn
An ex-Google, Stanford and Flipkart team
Rating Distribution
- 1 stars: 5 votes
- 2 stars: 6 votes
- 3 stars: 22 votes
- 4 stars: 33 votes
- 5 stars: 30 votes
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