Course Objective:
To make our trainee expert in the following topics theoretically & practically.
- Python Ecosystem
- Methods for Machine Learning
- Data Loading for ML Projects
- Understanding Data with Statistics
- Understanding Data with Visualization
- Data Feature Selection
- Logistic Regression
- Support Vector Machine (SVM)
- Decision Tree
- Naïve Bayes
- Random Forest
- Random Forest
- Linear Regression
- K-means Algorithm
- Mean Shift Algorithm
- Hierarchical Clustering
- Finding Nearest Neighbors
- Performance Metrics
- Automatic Workflows
- Improving Performance of ML Models
Note- We train our trainee until they are satisfied.
