From Start to Finish: NLP Project on Flipkart Reviews (2024) | Sentiment Analysis | Damks Analytics
442 بار بازدید -
2 ماه پیش
-
Welcome to our channel! Let's
Welcome to our channel! Let's assume I just landed a Data Scientist role at Flipkart, where I encountered a bunch of unrefined data. Flipkart, constantly gathering product reviews, recently because curious as to what could be done to the data to enhance their operations. Approached by my manager on potential improvements, one of my key suggestions was to develop a model capable of classifying reviews autonomously as "positive," "negative," or "neutral," seamlessly integrating this insight into their website. Such a model eliminates the need to manually read every review to gauge product performance.
In this project, you'll learn:
- How to efficiently load and manage a sample of Big Data in memory.
- Techniques to count categorical variables and visually explore data through visualization.
- Methods to create word clouds from textual data, offering intuitive insights.
- Best practices for splitting data into training and test sets for model validation.
- How to effectively vectorize text data for machine learning models.
- Steps to train classifiers like Multinomial Naive Bayes and RandomForest.
- Interpretation of model performance metrics such as "accuracy_score" and "classification_report."
- Guidelines on selecting models suitable for production deployment.
Join us on this project as we demonstrate practical data science techniques that can drive real-world impact. Don't forget to like, subscribe, and hit the notification bell to stay updated with our latest tutorials and projects!
LET'S GOOOOOOOO! (Vamos!)
Data source: https://www.kaggle.com/datasets/niral...
#sentimentanalysis #productreviews #nlp #naturallanguageprocessing #machinelearning #textclassification #datascience #datascienceproject #datavisualization #wordcloud #multinomial #naivebayes #randomforest #randomforests #classification #confusion #modeling #machinelearningwithpython #machinelearningjobs #machinelearningfullcourse #bigdata #bigdatatutorial #bigdataanalytics #bigdatatutorialforbeginners #trainingandtestsets #vectorizationinmachinelearning #python #pythonprogramming #pythontutorial #python3 #pythonforbeginners #pythonprojects #data #dataanalytics #dataanalysis #dataanalyst #datascientist
In this project, you'll learn:
- How to efficiently load and manage a sample of Big Data in memory.
- Techniques to count categorical variables and visually explore data through visualization.
- Methods to create word clouds from textual data, offering intuitive insights.
- Best practices for splitting data into training and test sets for model validation.
- How to effectively vectorize text data for machine learning models.
- Steps to train classifiers like Multinomial Naive Bayes and RandomForest.
- Interpretation of model performance metrics such as "accuracy_score" and "classification_report."
- Guidelines on selecting models suitable for production deployment.
Join us on this project as we demonstrate practical data science techniques that can drive real-world impact. Don't forget to like, subscribe, and hit the notification bell to stay updated with our latest tutorials and projects!
LET'S GOOOOOOOO! (Vamos!)
Data source: https://www.kaggle.com/datasets/niral...
#sentimentanalysis #productreviews #nlp #naturallanguageprocessing #machinelearning #textclassification #datascience #datascienceproject #datavisualization #wordcloud #multinomial #naivebayes #randomforest #randomforests #classification #confusion #modeling #machinelearningwithpython #machinelearningjobs #machinelearningfullcourse #bigdata #bigdatatutorial #bigdataanalytics #bigdatatutorialforbeginners #trainingandtestsets #vectorizationinmachinelearning #python #pythonprogramming #pythontutorial #python3 #pythonforbeginners #pythonprojects #data #dataanalytics #dataanalysis #dataanalyst #datascientist
2 ماه پیش
در تاریخ 1403/04/30 منتشر شده
است.
442
بـار بازدید شده