Portfolio Project: Predict Rating given Amazon Product Reviews using NLP
Learn how to use Python to predict ratings given Amazon product text reviews. Covers the foundational NLP concepts with intuition, theory and code demo. Practice using Python packages such as nltk, gensim, re, sklearn for various NLP tasks.
- Covers the foundational NLP concepts with intuition, theory and code demo
- Practice using Python packages such as nltk, gensim, re, sklearn for various NLP tasks
Prabhakaran SPrincipal Data Scientist
Included in All-Access, one membership for every course.
- Lessons
- 27, in 6 chapters
- Video
- 1 h 48 min
- Free to watch
- 6 lessons
- Certificate
- On completion
What you'll be able to do
- Foundational concepts of NLP
- Text Pre-processing steps for internet data
- Bag of Words Model
- TF-IDF based models
- Creating Unigrams, Bigrams and Trigrams with sklearn
- Training Word2Vec models
- Methods to approximate Word2Vec for sentences
Course content
6 chapters · 27 lessons · 1 h 48 min · 6 free to preview
01Sec 1: Introduction5 lessons · 19 min
- Understanding the DatasetPreview4:44
- Download Resources1:00
- Problem objective and framingPreview7:16
- Packages usedPreview2:06
- Load data and fix the scoresPreview3:56
02Sec 2: Exploratory Data Analysis (EDA) and Theory7 lessons · 25 min
- Data Cleaning - Fix duplicatesPreview7:38
- Why convert text to a vectorPreview3:34
- Bag of words model6:19
- Similarity3:35
- Disadvantages of BoW2:13
- Binary Bag of Words1:02
- Course Review1:00
03Sec 3: Text Processing5 lessons · 16 min
- Part 1 - Stop words2:02
- Part 2 - Why make it lower case1:03
- Part 3 - Stemming and Lemmatization3:22
- Code Demo - Preprocessing Review Text Data8:44
- Code Demo - Preprocessing Summary Text Data0:57
04Sec 4: Feature Engineering3 lessons · 13 min
- Code Demo - Bag of Words4:44
- Unigram, Bigrams and Trigrams5:11
- Code Demo - Create Bigrams and Trigrams2:48
05Sec 5: TFIDF3 lessons · 14 min
- What is TF-IDF and why.6:26
- Why use log in TFIDF.6:32
- Code Demo - TFIDF1:06
06Sec 6: Word2Vec4 lessons · 23 min
- Introduction to Word2Vec8:21
- Code Demo - Training Word2Vec4:59
- Averaging Word2Vec3:53
- TFIDF weighted Word2Vec5:43
What you need
- Basics of Python
- Foundational knowledge of Data Science
- High school maths
Who this course is for
- Data Science Aspirants
- Data Science Professionals
- Software/Data engineers interested in quantitative analysis
- Professionals working with large datasets
- Data analysts, economists, researchers
Your instructor

Prabhakaran S
Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this course!
I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.
I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!
- from 3,965 ratings
- 4.92
- learners
- 57K+
- courses
- 85
Questions
How do I get this course?
It is part of All-Access: one membership that opens all 85 courses. The plans and prices are on our course site. You can watch the free preview lessons before you join.
Can I get a refund?
Yes. If the membership is not right for you, ask for a refund within 30 days of your first payment.
Can I learn on my phone?
Yes. Lessons play in the browser on any phone, tablet or computer, and your place is saved for the next device.
I am already a member. Where are my courses?
On our course site, edu.machinelearningplus.com. Sign in there with the email you joined with. The courses move to this site later, with your access, and you will not pay again.