| 1. INTRODUCTION TO FLIPKART REVIEW SENTIMENT ANALYSIS.mp4 | 12.1 MB | ||
| 1. INTRODUCTION TO MACHINE LEARNING.mp4 | 25.5 MB | ||
| 1. INTRODUCTION TO YOUTUBE SPAM COMMENTS DETECTION.mp4 | 13 MB | ||
| 1.1 ml.mp4_en.mp4 | 10 MB | ||
| 2. SENTIMENT ANALYSIS CLASS 1 IMPORT PACKAGES.mp4 | 38.6 MB | ||
| 2. SPAM COMMENTS DETECTION CLASS 1 IMPORT PACKAGES.mp4 | 30.6 MB | ||
| 3. SENTIMENT ANALYSIS CLASS 2 IMPORT DATASET.mp4 | 40.8 MB | ||
| 3. SPAM COMMENTS DETECTION CLASS 2 IMPORT DATASET.mp4 | 44.3 MB | ||
| 3.1 flipkart_reviews.csv | 619 KB | ||
| 4. SENTIMENT ANALYSIS CLASS 3 CLEAN DATASET.mp4 | 49.1 MB | ||
| 4. SPAM COMMENTS DETECTION CLASS 3 SPLIT COLUMNS.mp4 | 12.5 MB | ||
| 5. SENTIMENT ANALYSIS CLASS 4 DATA VISULISATION.mp4 | 18.1 MB | ||
| 5. SPAM COMMENTS DETECTION CLASS 4 MAP COLUMNS.mp4 | 15.4 MB | ||
| 6. SENTIMENT ANALYSIS CLASS 5 TRAIN DATASET.mp4 | 42.8 MB | ||
| 6. SPAM COMMENTS DETECTION CLASS 5 TRAIN DATASET.mp4 | 41.9 MB | ||
| 7. SENTIMENT ANALYSIS CLASS 6 OUTPUT AND EXPLANATION.mp4 | 14.9 MB | ||
| 7. SPAM COMMENTS DETECTION CLASS 6 OUTPUT.mp4 | 29.9 MB | ||
| 8. MACHINE LEARNING QUIZ.html | 204.8 B | ||
| 8. SENTIMENT ANALYSIS CLASS 7 CONCLUSION.mp4 | 20.7 MB | ||
| 9. MACHINE LEARNING ASSIGNMENT.html | 204.8 B | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 22 total files | |||
Flipkart Review Sentiment Analysis & Spam Comments Detection
https://DevCourseWeb.com
Published 4/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 11m | Size: 461 MB
Complete Flipkart Review Sentiment Analysis & Spam Comments Detection
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.
Requirements
Familiarity with data preprocessing and machine learning libraries such as scikit-learn.
Access to a computer with internet connectivity and Python environment setup.
All Comments