Machine learning studies

Models of machine learning
- Supervised learning
  - Binary classification Validation:
    - Cross validation (KFold)
    - Shuffle KFold
    - Stratified KFold
    - GroupKFold
    - Pipeline
    - GridSearchCV and RandomizedSearchCV for optimization of hyper-parameters
  Scikit:
  - Linear Support Vector Classification (Linear SVC)
  - Support Vector Classification (SVC)
  - Decision tree Classsifier
  - Dummy Classifier
  - Multinomial Naive Bayes
  - AdaBoost Classifier Multidimensional data:
    - Random Forest Classifier
    - Random Forest with SelectKBest
    - Evaluate results with Confusion Matrix
    - Random Forest with RFE (Recursive feature elimination)
    - Random Forest with RFECV (Cross-validation estimator)
    - Random Forest with PCA
    - Random Forest with TSNE
- Unsupervised learning
  - K-Means
  - DBSCAN
  - Meanshift
  - Silhouette coefficient
  - Davies bouldin index calculation
  - Calinski Harabasz index calculation Validation:
    - Relative validation
    - Cluster structure validation
    - Cluster stability validation
- Deep Learning Keras with Tensorflow - ReLu - Softmax - Export model to .h5 file PyTorch - ReLU - Perceptron - MLP (Multi-layer perceptron)
- MLOps Create a web api to use a ml model using Flask and pickle
- NLP
  - MLE
  - LaPlace
  - NLTK
  - Bigrams
  - Language detection
  - tokenizers