Enrolment options
Udemy - No-Code Machine Learning Practical Guide to Modern ML Tools 2021-6
Course modified date: 9 Feb 2024
- Enrolled students: There are no students enrolled in this course.
Guests cannot access this course. Please log in.
Udemy - No-Code Machine Learning Practical Guide to Modern ML Tools 2021-6
Course content
Sections:
6
•
Activities:
0
•
Resources:
39
- 1. Introduction and Welcome Message
- 2. Best Practices, Success Tips and Certification
- 3. Artificial Intelligence (AI) and Machine Learning (ML) Super Powers
- 4. Machine Learning The Big Picture
- 5. Machine Learning Key Elements (Recipe!)
- Docs
- 1. The Rise of Machine Learning in Higher Education
- 2. Machine Learning Regression 101
- 3. Google Vertex AI Demo Part 1 Setup and Upload
- 4. Google Vertex AI Demo Part 2 Model Training
- 5. Machine Learning Regression Models Metrics
- 6. Google Vertex AI Demo Part 3 Test and Deploy Trained Model
- 7. Recap and Concluding Remarks
- 1. Introduction to Machine Learning in FinanceBanking
- 2. Project Overview Bank Loan Risk Prediction
- 4. Data Robot Demo Part #2 Target Selection and Exploratory Data Analysis
- 5. Data Robot Demo Part 3 Model Training and Feature Importance
- 6. Data Robot Demo Part 4 Confusion Matrix, Precision, Recall, ROC, AUC
- 7. Data Robot Demo Part #5 Model Assessment
- 8. Data Robot Demo Part 6 Hyper Parameters Tuning
- 9. Data Robot Demo Part 7 Model Deployment and Making Inference
- 10. Project Recap and Concluding Remarks
- 1. Introduction to Machine Learning for Price Prediction
- 2. Project Overview
- 3. Microsoft Azure ML Demo Part #1 ML Signup and Studio Launch
- 4. Microsoft Azure ML Demo Part #2 Dataset Creation
- 5. Microsoft Azure ML Demo Part #3 Build ML Pipeline with ML Azure Designer
- 6. Microsoft Azure ML Demo Part #4 Execute and Test the Pipeline
- 7. Microsoft Azure ML Demo Part #5 Deploy Model and Make Inference
- 8. Mini Project Build and Test Multiple Models
- 9. Mini Project Solution Build and Test Multiple Models
- 10. Project Recap and Concluding Remarks
- 1. Thanks for Watching!
- 1. Introduction to XG-Boost [Optional LectureAdditional Material]
- 2. What is boosting
- 3. Decision trees and ensemble learning
- 4. Gradient Boosting Deep Dive #1 [Optional LectureAdditional Material]
- 5. Gradient Boosting Deep Dive #2 [Optional LectureAdditional Material]
- 6. AWS SageMaker XGBoost