Disclosure: when you buy through links on our site, we may earn an affiliate commission.

Project Based Text Mining in Python

The basic operations related to structuring the unstructured data into vector and reading different types of data from the public archives are taught.
/5
Created by

8.7

CourseMarks Score®

9.5

Freshness

N/A

Feedback

7.5

Content

Platform: Simpliv Learning
Price: $9.99
Video: 5h25m
Language: English
Next start: On Demand

Top Machine Learning courses:

Detailed Analysis

CourseMarks Score®

8.7 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.5 / 10
This course was last updated on 11/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

We analyzed factors such as the rating and the ratio between the number of reviews and the number of students, which is a great signal of student commitment. If a course does not yet have a rating, we exclude Feedback Score from the overall CourseMarks Score.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

7.5 / 10
Video Score: 7.6 / 10
The course includes 5h25m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 15 minutes of 454 Machine Learning courses on Simpliv Learning.
Detail Score: 9.3 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

In this course, we study the basics of text mining.

The basic operations related to structuring the unstructured data into vector and reading different types of data from the public archives are taught.

Building on it we use Natural Language Processing for pre-processing our dataset.

Machine Learning techniques are used for document classification, clustering and the evaluation of their models.

Information Extraction part is covered with the help of Topic modeling

Sentiment Analysis with a classifier and dictionary based approach

Almost all modules are supported with assignments to practice.

Two projects are given that make use of most of the topics separately covered in these modules.

Finally, a list of possible project suggestions are given for students to choose from and build their own project.

Basic knowledge
Basics of programming (Any language, python is a bonus)
Basic understanding of Machine Learning
Can code with lists, loops and conditions and have basic understanding of models learning patterns from data

You will learn

What will you learn
✓ In this course the students will learn the basics of text mining and will build on it to perform document categorization, document grouping and sentiment analysis
✓ The practicals are carried out in Python language, Natural Language Processing (NLP) is used for pre-processing
✓ Starting from a very small dummy dataset, we migrate to existing databases and then to building a database of your own to performed text mining tasks
✓ Sentiment analysis of user hotel reviews

Requirements

• Basics of programming (Any language, python is a bonus)
• Basic understanding of Machine Learning
• Can code with lists, loops and conditions and have basic understanding of models learning patterns from data

This course is for

• Beginners in python and curious about data science
• Knows programming in Python and basic concepts of Data Science but cannot practically relate the two

How much does the Project Based Text Mining in Python course cost? Is it worth it?

The course costs $9.99. And currently there is a 80% discount on the original price of the course, which was $49.99. So you save $40 if you enroll the course now.
The average price is $17.2 of 454 Machine Learning courses. So this course is -42% more expensive than the average Machine Learning course on Simpliv Learning.

Does the Project Based Text Mining in Python course have a money back guarantee or refund policy?

YES, Project Based Text Mining in Python has a 20-day money back guarantee. The 20-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Project Based Text Mining in Python course, but there is a $40 discount from the original price ($49.99). So the current price is just $9.99.

Who is the instructor? Is Muhammad Taimoor Khan a SCAM or a TRUSTED instructor?

Muhammad Taimoor Khan has created 1 courses that got 0 reviews which are generally positive. Muhammad Taimoor Khan has taught 0 students and received a average review out of 0 reviews. Depending on the information available, Muhammad Taimoor Khan is a TRUSTED instructor.

8.7

CourseMarks Score®

9.5

Freshness

N/A

Feedback

7.5

Content

Platform: Simpliv Learning
Price: $9.99
Video: 5h25m
Language: English
Next start: On Demand

Students are also interested in

Get this widget on your website (for course creators):

Project Based Text Mining in Python rating
Copy this code and paste it to your website:
<a href="https://coursemarks.com/course/project-based-text-mining-in-python-2/" target="_blank" title="Project Based Text Mining in Python on Coursemarks.com"><img border="0" src="https://coursemarks.com/widget/88.svg" width="200px" alt="Project Based Text Mining in Python rating"/></a>