HomeFree Course Flipkart Review Sentiment Analysis & Spam Comments Detection Free Course Coupon

 Flipkart Review Sentiment Analysis & Spam Comments Detection Free Course Coupon

Sentiment Analysis, NLP, Machine Learning, Spam Detection, Flipkart Reviews, Data Cleaning, Model Deployment, Feature Extraction, Text Vectorization

Master sentiment analysis and spam comment detection with real-world Flipkart review data. Learn NLP, data cleaning, and machine learning techniques to gain valuable insights from customer feedback.

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Course DescriptionDetails
Company NameUdemy
Course NameFlipkart Review Sentiment Analysis & Spam Comments Detection
Coupon Code5AEF31839BB63C7D3C11
Course Duration1 hour on-demand video
AccessAccess on mobile and TV
Lifetime AccessYes
Certificate of completionYes
 Flipkart Review Sentiment Analysis & Spam Comments Detection Free Course Coupon

What you’ll learn

  • you’ll learn how to leverage machine learning techniques to analyze sentiments
  • Handle data cleaning tasks such as removing duplicates, handling missing values, and tokenizing text.
  • Experiment with different algorithms and evaluate their performance using appropriate metrics.
  • Learn approaches to interpret and explain model predictions in the context of sentiment analysis

This course includes:

  • 1 hour on-demand video
  • Assignments
  • 2 downloadable resources
  • Access on mobile and TV
  • Full lifetime access
  • Certificate of completion

Description

Course Title: Flipkart Review Sentiment Analysis & Spam Comments Detection

Course Description:

Also Check Below  content

Welcome to the “Flipkart Review Sentiment Analysis & Spam Comments Detection” course! In this hands-on course, you’ll delve into the fascinating world of natural language processing (NLP) and machine learning by exploring how to analyze sentiment in product reviews on Flipkart, one of India’s leading e-commerce platforms. You’ll learn how to build robust models to classify reviews into positive, negative, or neutral sentiments, as well as detect spam comments, helping businesses gain valuable insights from customer feedback.

What You Will Learn:

  1. Introduction to Sentiment Analysis:
    • Understand the importance of sentiment analysis in extracting insights from text data.
    • Learn about the applications and challenges of sentiment analysis in real-world scenarios.
  2. Flipkart Review Data Collection:
    • Explore methods to collect Flipkart product reviews using web scraping techniques.
    • Learn how to extract relevant information from CSV and organize it for analysis.
  3. Preprocessing and Text Cleaning:
    • Dive into text preprocessing techniques to clean and normalize review data.
    • Remove noise, handle special characters, and tokenize text for further analysis.
  4. Feature Extraction and Vectorization:
    • Understand the concept of feature extraction and vectorization in NLP.
  5. Sentiment Analysis Models:
    • Learn how to build machine learning and deep learning models for sentiment analysis.
    • Experiment with algorithms such as Naive Bayes
  6. Evaluation Metrics for Sentiment Analysis:
    • Explore evaluation metrics such as accuracy, precision, recall, and F1-score for model performance assessment.
    • Understand how to interpret confusion matrices and ROC curves in the context of sentiment analysis.
  7. Spam Comments Detection:
    • Learn techniques to identify and filter out spam comments from product reviews.
    • Implement rule-based and machine learning approaches to detect spam patterns and outliers.
  8. Model Deployment and Integration:
    • Explore methods to deploy sentiment analysis models in production environments.
    • Integrate models with web applications or APIs for real-time sentiment analysis.
  9. Performance Optimization and Scalability:
    • Learn strategies to optimize model performance and scalability for handling large volumes of data.
    • Explore techniques such as batch processing and parallel computing.
  10. Ethical Considerations and Best Practices:
    • Discuss ethical considerations in sentiment analysis, including privacy concerns and bias mitigation.
    • Learn best practices for responsible data collection, model development, and deployment.

Why Enroll:

  • Practical Application: Gain hands-on experience by working with real-world Flipkart review data.
  • Project-Based Learning: Build end-to-end sentiment analysis and spam detection models from scratch.
  • Career Advancement: NLP and sentiment analysis skills are in high demand across various industries, offering opportunities for career growth and specialization.

Embark on this exciting journey into sentiment analysis and spam detection with Flipkart reviews, and gain valuable insights from customer feedback. Enroll now to enhance your NLP skills and become proficient in extracting actionable insights from textual data!

Who this course is for:

  • Developers looking to integrate sentiment analysis capabilities into their applications.
  • Data enthusiasts interested in applying machine learning to analyze textual data.

How to Get this course FREE?

Get a 100% Discount On Udemy courses by clicking on the Apply Here Button. This Course coupon code is automatically added to the Apply Here Button.

Apply this Coupon:  5AEF31839BB63C7D3C11    is applied  (For 100% Discount)

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Pratik Nagda
Pratik Nagdahttp://careerboostzone.com
My name is Pratik Nagda and I am a resident of the small town of Nallasopara in Maharashtra. I come from a very poor family and I live with my mom. My father was dead when I was in 4th grade. Due to that financial issue, I was forced to go to a hostel from the 5th to the 10th. I know the basics of blogging and all because in my final year of school, after that, when I came home, I had a great fight with my mom because she wanted to take me science and I wanted to take science. Finally, I convinced my mom. I have done engineering at St. John College of Engineering and Management, which is in Palghar. I still love my college very much. Even today, I keep sharing the experiences of my college with my readers. Today I am the owner of the CareerBoostZone English blogging site and through my blog, I have prepared a better employment platform for Readers I feel happy that I tried to empower readers by helping in employment and the development of the country. And my efforts are continuing towards success.
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