Belhard data science

1. HW1 task : utilize a dataset on electricity consumption and train a regression model to forecast future consumption.
2. HW2 includs :
   1. Clustering task : perform hierarchical clustering and DBSCAN using the example of a dataset on the distribution of penguins by type. Use UMAP & LDA to reduce feature space.
   2. Autoencoder task : create an autoencoder for dimensionality reduction of molecular illustrations in chemical education.
3. HW3 use mlflow to investigate models properties and solve next tasks :
   1. Binary classification task : solve binary classification task using pycaret AutoML.
   2. Multiclass classification task : solve multiclass classification task using pycaret AutoML.
   3. Clustering task : solve clustering task using pycaret AutoML.
   4. Regression task : solve regression task using pycaret AutoML.
   5. NLP multiclass classification : solve NLP multiclass classification task using pycaret AutoML.
4. HW4 task : create a reinforcement learning neural network model and apply hyperparameter tuning to this model.
5. HW5 task : train yolov5 model on base & custom datasets.
6. HW6 task : Create a neural network model to predict the next frame in an animated cartoon. Let's compare a transformer model with a non-transformer model.