Machine Learning դասընթաց սկսնակների համար

- Variables, arithmetic operations
- Strings
- If, elif, else statements
- Lists, tuples, dictionaries
- For, while loops
- Functions
- Lambda and higher-order functions
- Classes
- OOP principles
- File handling
- Exception handling
- Standard library:

- Numpy
- Pandas
- Matplotlib | Plotly
- Scikit learn
- Tensorflow (Keras)
- Streamlit:

- K Nearest Neighbors
- Linear Regression
- Logistic Regression
- Multilayer Perceptron
- Decision Trees
- Bagging | Boosting
- Clustering
- Dimensionality reduction:

- Underfitting/overfitting
- Optimizers (Gradient descent, GD with momentum, RMSProp, Adam)
- Regularization (L1, L2 norms, dropout, early stopping)
- Evaluation metrics:

- Intro to Computer Vision
- Intro to Convolutional Neural Networks
- Intro to Recurrent Neural Networks
- Intro to Reinforcement Learning
- Explainable AI:

- Git
- Jupyter notebook
- Code deployment:

Դասընթացի վերջում մասնակիցները կստանան դասընթացի մասնակցության վկայականներ: