guilherme-alves-silve / machine-learning-python

Estudo de Machine Learning com Python

Intro

• Machine Learning: introdução a classificação com SKLearn
  • intro/introducao_classificacao_ml_1.ipynb
  • intro/introducao_classificacao_ml_2.ipynb
  • intro/introducao_classificacao_ml_3.ipynb
  • intro/introducao_classificacao_ml_4.ipynb

Clustering

• Clustering Básico: k-means, DBSCAN e mean shift
  • cluster/clustering_basico.ipynb
• Machine Learning: classificação por trás dos panos
  • cluster/ml_classificacao_por_de_tras_dos_panos.ipynb
• Clusterização de dados: segmentação de clientes
  • cluster/clusterizacao_clientes_rfm_ml.ipynb
• Análise de componentes principais: elaboração de rankings com o PCA
  • .ipynb

Multi Layer Perceptron & Support Vector Machines

• Machine Learning: Credit Scoring
  • mlp/machine_learning_credit_scoring.ipynb
• Keras Regression (Houses Price)
  • mlp/ann_regression_keras.ipynb
• Keras Classification (Cancer)
  • mlp/ann_classification_keras.ipynb
• Keras Classification Exercise (Lending Money)
  • mlp/ann_keras_project_exercise.ipynb
• Machine Learning: Aprendizado supervisionado
  • .ipynb

Convolutional Neural Network

• Keras CNN Classification (MNIST Digits)
  • cnn/cnn_keras_mnist.ipynb
• Keras CNN Classification (CIFAR-10)
  • cnn/cnn_keras_cifar10.ipynb
• Keras CNN Classification (Malaria Infection)
  • cnn/cnn_keras_cell.ipynb
• Keras CNN Classification (Fashion MNIST)
  • cnn/cnn_keras_project_exercise_fashion_mnist.ipynb
• Machine Learning: Aprendizado supervisionado
  • .ipynb

Decision Trees

• Árvores de Decisão: aprofundando em modelos de Machine Learning
  • tree/machine_learning_decision_tree.ipynb

Validations

• Boruta - auto feature selection
  • validation/boruta.ipynb
• Handling Imbalanced Datasets SMOTE Technique
  • validation/imbalance_dataset_smote.ipynb
• Machine Learning: validação de modelos
  • validation/ml_validacao_1.ipynb

Time Series

• Análise de série temporal: COVID-19
  • time_series/analise_serie_temporal_covid_19.ipynb

Natural Language Processing

• Linguagem Natural parte 1: NLP com análise de sentimento
  • nlp/ml_linguagem_natural_1.ipynb
• Linguagem Natural parte 2: continuando com a análise de sentimento
  • nlp/ml_linguagem_natural_2.ipynb
• Corretor Ortográfico em Python: aplicando técnicas de NLP
  • nlp/corretor_nlp.ipynb
• NLP: regex e modelos de linguagem
  • nlp/detector-idiomas-nlp.ipynb
• Word2Vec: interpretação da linguagem humana com Word embedding
  • nlp/curso_word2vec_1.ipynb
• Word2Vec: treinamento de Word Embedding
  • nlp/curso_word2vec_2.ipynb
  • nlp/classificador_de_artigos/
    • python3 app.py
    • localhost:5000
• Markov Chains
  • Markov Chains Clearly Explained! Part - 1
  • Markov Chains: Recurrence, Irreducibility, Classes | Part - 2
  • Markov Chains: n-step Transition Matrix | Part - 3
  • Markov Chains: Generating Sherlock Holmes Stories | Part - 4
  • Hidden Markov Model Clearly Explained! Part - 5
  • Forward Algorithm Clearly Explained | Hidden Markov Model | Part - 6
  • Markov Chains: Simulation in Python | Stationary Distribution Computation | Part - 7
• Classificação multilabel de textos: múltiplos contextos em NLP
  • nlp/classificacao_multi_label_nlp.ipynb

Reinforcement Learning

• Q-Learning implementation (Tic Tac Toe)
  • rf_lr/qlearning/tictactoe
• Deep Q-Learning implementation (Tic Tac Toe)
  • rf_lr/deepqlearning/tictactoe
• Learn how to use Reinforcement Learning techniques to create practical Artificial Intelligence programs!
  • rf_lr/qlearning/intro_rflr_gym.ipynb
  • rf_lr/qlearning/agent_rflr_gym.ipynb
  • rf_lr/qlearning/simple_agent_rflr_gym.ipynb
  • rf_lr/qlearning/q_learning_rflr_gym.ipynb
  • rf_lr/qlearning/q_learning_continuous_rflr_gym.ipynb
  • rf_lr/qlearning/q_learning_exercise.ipynb
  • rf_lr/qlearning/q_learning_route.ipynb
  • rf_lr/deepqlearning/deep_q_learning_rflr_gym
  • rf_lr/deepqlearning/deep_q_learning_rflr_gym_keras_rl2.ipynb
  • rf_lr/deepqlearning/deep_q_learning_rflr_gym_keras_rl2_exercise.ipynb
  • rf_lr/deepqlearning/deep_q_learning_image_rflr_gym_keras_rl2.ipynb
  • rf_lr/deepqlearning/deep_q_learning_image_rflr_gym_keras_rl2_exercise.ipynb
  • rf_lr/deepqlearning/deep_q_learning_rflr_custom_snake_gym_keras_rl2.ipynb
• Inteligência Artificial aplicada para Empresas e Negócios
  • rf_lr/qlearning/q_learning_route.ipynb
  • rf_lr/deepqlearning/deep_q_learning_server_cost_minimization.ipynb
  • rf_lr/mab/thompson_sampling.ipynb
    • mab - Multi Armed Bandit (Thompson Sampling)
• Deep RL Course

From scratch series - Patrick Loeber course

• KNN
  • .py
• Linear Regression
  • .py
• Logistic Regression
  • .py
• Linear and Logistic Regression
  • .py
• Naive Bayes
  • .py
• Perceptron
  • .py
• SVM
  • .py
• Decision Tree
  • .py
• Random Forest
  • .py
• PCA
  • .py
• K-Means
  • scratch/kmeans.ipynb
• AdaBoost
  • .py
• LDA (Linear Discriminant Analysis)
  • .py
• How to Load Machine Learning Data From Files
  • .py