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Course Outline
Module I: Regression Models
1. Basics of regression with a linear model example
2. Optimization using the least squares method
3. Practical implementation using scikit-learn
4. Metrics for evaluating regression models
5. Overview of other regression methods
Module II: Data Preparation for Modeling
1. Feature engineering
2. Scaling and standardizing variables
3. Identifying and eliminating outliers
4. Strategies for imputing missing values
5. Methods for dimensionality reduction and feature selection
6. Encoding categorical variables (one-hot encoding, label encoding)
Module III: The Problem of Overfitting Models
1. The phenomenon of overfitting and its consequences
2. Techniques to prevent overfitting
3. Cross-validation as a tool for model evaluation
4. Regularization of machine learning models
Module IV: Optimizing the Learning Process
1. Hyperparameter tuning using grid search
2. Building data processing pipelines
Module V: Classification Algorithms
1. Introduction to classification using logistic regression
2. Comparing linear and non-linear models
3. Metrics for evaluating classifier quality
4. Decision tree algorithm
5. Naive Bayes classifier
6. Support Vector Machine (SVM)
7. K-Nearest Neighbors (KNN) method
8. Issues in multi-class classification
9. Ensemble methods – Random Forest and Gradient Boosting
21 Hours
Testimonials (5)
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
Jenna - TCMT
Course - Machine Learning with Python – 2 Days
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI
The explaination
Wei Yang Teo - Ministry of Defence, Singapore
Course - Machine Learning with Python – 4 Days
Trainer develops training based on participant's pace
