F.U.N With Machine Learning
June 20, 2020
14:00 - 16:30 Asia/Kolkata
”If you don’t have the courage and will power to turn your idea into a reality, then you always stay as a daydreamer.”
We are here to push you towards your dreams!
A very warm welcome to our club CODEZILLA.
Hope you and your family doing well during this tough times!
We are back again with another interesting event to add something new to your skill list .
Codezilla presents :
F.U.N. WITH Machine Learning (Face Unsupervised Network Algorithm)
The idea behind this event is to empower students with the recent advancements in Internet Generation .A webinar on FACIAL UNSUPERVISED NETWORK (F.U.N).
This webinar will help you to understand how facial supervised nework works with ML. The session’s goal is to provide every individual innovative ideas so that they can acquire some high-yielding knowledge.
The only fence against the world is through knowledge. Be a part of the event and learn about this interesting field.
DATE: July 20 ,2020.
Hurry up and register here: http://codezilla.club/event-registration-form-2/
• Introduction to the project
• System and Requirements
• Links and other documents
2. Short discussion on importing libraries for this project
• Python Libraries for this project
• Importing libraries
• Small explanation to these libraries
3. (Short Break)
4. Reading of target images into the project
• Acquiring and reading images into the project
• Creating arrays to hold image data
5. Image pre-processing
• Resizing of images
• Converting of images into greyscale
6. (Short Break)
7. Assembly of Dataset
• Creation of Pandas Data Frames from image arrays
• Assembly of above data frames into single data frame
• (Optional) Saving of final Data Frame
8. Post-Processing of data for machine learning
• Splitting of Dataset into training and testing data
• Explanation of why this is needed
9. (Short Break)
10. The SVC Technique
• Basic explanation of Supervised Learning
• Explanation of SVC Technique
11. Using SVC in our project
• Coding the SVC Technique
• Testing Models
• Checking Accuracy
We will learn:
1. Introduction to machine learning with python
2. Setting up python for ML
3. Learn to convert data
4. Learn to process data
5. Train and tweak the model