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PRACTICAL AI & Deep
Learning
Computer Vision and
Image Processing
CRISP-ML(Q) : Cross
Industry Standard
Process for Data Mining
1. Understand Business
Problem & Create
Project Charter
2. Data Collection
3. Data Cleansing /
Preparation / EDA /
Feature Engineering
4. Data Mining /
Machine Learning
5. Model Evaluation
6. Model Deployment
Deep Learning Primer
Mathematical
Foundations
Deep Learning
Challenges & Practical
Issues
Inferential Statistics
Probability
Distributions
Convolution Neural
Network (CNN)
Object Detection
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