p-ferreira / machine-learning-studies

Machine learning studies

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