- Numpy, Pandas, Sklearn, Seaborn, Matplotlib
- Pandas Profiling
- Exploratory Data Analysis
- Data collection, labeling and save
- Supervised, Unsupervised Training Methods
- Linear and Logistic Regression
- Decision Tree and Random Forest
- Clustering, KNN, DBScan
- Dimensionality Reduction
- Introduction to Neural Networks, Loss, Activation, Optimizer
- se of Keras, Tensorflow, Pytorch libraries
- Classification and Regression with Keras
- RNN, LSTM
- Introduction to NLP