Machine Learning
د.ت250
Upcoming Course
Cohort 2021: August 1st to August 20, 2021
- Live classroom with the instructor (check out the timetable below)
- 15+ models with detailed case studies
- Live coding in your browser
Machine Learning
This course will guide through the must know ML models and how to efficiently create an ML pipeline in order to extract intelligence from data. You will work on various datasets to understand the importance of domain knowledge as well how to evaluate the performance of your models.
Case Studies
Detailed tutorials how to effectively create your ML pipeline on wide range of datasets.
Challenge exam and certificate
A certificate of completion will be awarded when you complete the ML training.
Course Features
- Lectures 27
- Quizzes 0
- Duration 20 Hours
- Skill level All levels
- Language English
- Students 1
- Assessments Self
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Section 1: Building Blocks of Machine Learning Models
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Section 2: Regression-Based Learning
- Linear regression
- Let’s Practice: Fuel Consumption: Simple Linear Regression (1hr)
- Multiple Linear Regression (Theory & Guided Project)
- Let’s Practice: Multiple Linear Regression: Fuel Consumption: (1hr)
- Let’s Practice: Polynomial Regression: CO2 (1hr)
- Let’s Practice: Non-linear Reg: China’s GDP (1hr)
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Section 3: Classification
- Classification and prediction
- Logistic Regression
- Let’s Practice: Logistic Reg. Model: Diabetes in India (1hr)
- Let’s Practice: Logistic regression and z testing – Heart disease
- K-Nearest Neighbors: Theory & Guided Project
- Let’s Practice: K-NN: Telecom Data (1hr)
- Decision Tree
- Decision Tree: Theory & Guided Project
- Let’s Practice: Decision Tree: Patients & Drugs (1hr)
- Let’s Practice: Decision Tree: Model Performance Evaluation
- SVM Classifier: Theory & Guided Project
- Very Important-Graded Lab!!!: Malign/Benign Human Cell SVM Classifier
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Section 4: Clustering Techniques
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Section 5: Applications
