Support Vector Machines in Python, From Start to Finish
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- Offered byCoursera
Support Vector Machines in Python, From Start to Finish at Coursera Overview
Support Vector Machines in Python, From Start to Finish
at Coursera
Learn by doing through completing tasks in a split-screen environment directly in your browser
Duration | 2 hours |
Total fee | ₹729 |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Credential | Certificate |
Support Vector Machines in Python, From Start to Finish at Coursera Highlights
Support Vector Machines in Python, From Start to Finish
at Coursera
- Get free download of created material
- Students can access their cloud desktop across six different sessions
- Get instant access to the necessary software packages through Rhyme
- A split-screen video walkthrough of each step, from a subject-matter expert
- Learn from all learning materials, including the interactive workspace and final quiz
Read more
Support Vector Machines in Python, From Start to Finish at Coursera Course details
Support Vector Machines in Python, From Start to Finish
at Coursera
Skills you will learn
Who should do this course?
- For learners who are based in the North America region
What are the course deliverables?
- Import data into, and manipulating a pandas dataframe
- Format the data for a support vector machine, including One-Hot Encoding and missing data.
- Optimize parameters for the radial basis function and classification
- Build, evaluate, draw and interpret a support vector machine
More about this course
- This course runs on Coursera's hands-on project platform called Rhyme
- On Rhyme, students do projects in a hands-on manner in your browser
- Get instant access to pre-configured cloud desktops containing all of the software and data you need for the project.
- Everything is already set up directly in Internet browser so you can just focus on learning
- For this project, students will get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed
Support Vector Machines in Python, From Start to Finish at Coursera Curriculum
Support Vector Machines in Python, From Start to Finish
at Coursera
Import the modules that will do all the work
Import the data
Missing Data Part 1: Identifying Missing Data
Missing Data Part 2: Dealing With Missing Data
Format Data Part 1: Split the Data into Dependent and Independent Variables
Format the Data Part 2: One-Hot Encoding
Format the Data Part 3: Centering and Scaling
Build A Preliminary Support Vector Machine
Optimize Parameters with Cross Validation
Building, Evaluating, Drawing, and Interpreting the Final Support Vector Machine
Support Vector Machines in Python, From Start to Finish at Coursera Faculty details
Support Vector Machines in Python, From Start to Finish
at Coursera
Josh Starmer
Josh Starmer makes StatQuest videos on statistics and machine learning. Before that he did computational bio-stuff (statistics, mathematics, computing etc) at the University of North Carolina at Chapel Hill
Support Vector Machines in Python, From Start to Finish at Coursera Entry Requirements
Support Vector Machines in Python, From Start to Finish
at Coursera
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Support Vector Machines in Python, From Start to Finish at Coursera Students Ratings & Reviews
Support Vector Machines in Python, From Start to Finish
at Coursera
3/5
1 Rating- 2-31
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ROHAN LONE
Support Vector Machines in Python, From Start to Finish
Offered by Coursera
3
Other: Understood the theory behind support vector machines Built SVM models with scikit-learn to classify linear and non-linear data Determined the strengths and limitations of SVMs
Reviewed on 19 Sep 2021Read More
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Support Vector Machines in Python, From Start to Finish
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