(eCornell) Classifying Documents With Supervised Machine Learning

Training Provider: GENASHTIM
Course Reference: TGS-2023038319
S$1,000

About This Course

In this course, you will start to use machine learning methods to further your exploration of document term matrices (DTM). You will use a DTM to create train and test sets with the scikit-learn package in Python � an important first step in categorizing different documents. You will also examine different models, determining how to select the most appropriate model for your particular natural language processing task. Finally, after you have chosen a model, trained it, and tested it, you will work with several evaluation metrics to measure how well your model performed. The technical skills and evaluation processes you study in the course will provide valuable experience for the workplace and beyond. The course is provided by eCornell in partnership with Genashtim.

What You'll Learn

Create train and test sets from document term matrices
Train classification models to categorize documents
Evaluate the model on the test set to measure how well it generalizes

Course Details

Duration 15 hours
Language English
Training Commitment Part Time
Total Enrolled New course
Back to All Courses
Note: To apply for this course, visit the SkillsFuture website or contact the training provider directly.

More Courses from GENASHTIM

The framework used in this course for solving fluid dynamics problems can be applied to a wide array...
Duration 12 hours
Fee After Subsidy S$700
While 2D simulations are a good place to begin, many of the real-world applications of simulation re...
Duration 12 hours
Fee After Subsidy S$700
In this course, you will analyze the processes and theories you must consider as you begin to explor...
Duration 12 hours
Fee After Subsidy S$700