GitHub - Anello92/machine_learning: Key Concepts and Approaches in Machine Learning with R & Python: Covering essential methodologies such as ARIMA, regression, regularization, classification, k-nearest neighbors (kNN), decision trees, exploratory data analysis, recommendation systems, and gradient boosting techniques.

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Key Concepts and Approaches in Machine Learning with R & Python: Covering essential methodologies such as ARIMA, regression, regularization, classification, k-nearest neighbors (kNN), decision trees, exploratory data analysis, recommendation systems, and gradient boosting techniques.

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Name		Name	Last commit message	Last commit date
Latest commit History 103 Commits
00_Cap00_Bibliotecas_Python.ipynb		00_Cap00_Bibliotecas_Python.ipynb
ARIMA_Series_Temporais.ipynb		ARIMA_Series_Temporais.ipynb
Cap01_Matematica_Machine_Learning.ipynb		Cap01_Matematica_Machine_Learning.ipynb
Cap02_Features_Engineering_Categorical_DuummyVars.ipynb		Cap02_Features_Engineering_Categorical_DuummyVars.ipynb
Cap04-Conceito-Regressao-Peso-Cerebro.ipynb		Cap04-Conceito-Regressao-Peso-Cerebro.ipynb
Cap04-Conceitos-Regressao-Machine-Learning.ipynb		Cap04-Conceitos-Regressao-Machine-Learning.ipynb
Cap04-Regressao-Apostila-Machine-Learning.ipynb		Cap04-Regressao-Apostila-Machine-Learning.ipynb
Cap05-Regularizacao-Lasso-Ridge.ipynb		Cap05-Regularizacao-Lasso-Ridge.ipynb
Cap05-Risco_Credito_Reg_Logistica.ipynb		Cap05-Risco_Credito_Reg_Logistica.ipynb
Cap06-ClassificacaoKNN.ipynb		Cap06-ClassificacaoKNN.ipynb
Cap07_Sistemas_Equacoes_Lineares.ipynb		Cap07_Sistemas_Equacoes_Lineares.ipynb
Cap08-05-Scikit-Learn.ipynb		Cap08-05-Scikit-Learn.ipynb
Cap08_Arvore_Decisao_Prune.ipynb		Cap08_Arvore_Decisao_Prune.ipynb
Cap08_Arvore_Decisao_Rpart.ipynb		Cap08_Arvore_Decisao_Rpart.ipynb
Cap08_KNN_R_Classificacao.ipynb		Cap08_KNN_R_Classificacao.ipynb
Cap08_Risco_Credito_Modelo_Decisao.ipynb		Cap08_Risco_Credito_Modelo_Decisao.ipynb
Cap09-DecisionTree-Python.ipynb		Cap09-DecisionTree-Python.ipynb
Cap10-DBSCAN.ipynb		Cap10-DBSCAN.ipynb
Cap10-K-Means.ipynb		Cap10-K-Means.ipynb
Cap10-Mean-Shift.ipynb		Cap10-Mean-Shift.ipynb
Cap10-Spark-Streaming-Intro.ipynb		Cap10-Spark-Streaming-Intro.ipynb
Cap10-Spark-Streaming-Twitter.ipynb		Cap10-Spark-Streaming-Twitter.ipynb
Cap10_Segmentacao_Consumidores_Campanha_Marketing.ipynb		Cap10_Segmentacao_Consumidores_Campanha_Marketing.ipynb
Cap11-Spark-MLLib-Clustering-K-Means.ipynb		Cap11-Spark-MLLib-Clustering-K-Means.ipynb
Cap11-Spark-MLLib-DecisionTree.ipynb		Cap11-Spark-MLLib-DecisionTree.ipynb
Cap11-Spark-MLLib-NaiveBayes.ipynb		Cap11-Spark-MLLib-NaiveBayes.ipynb
Cap11-Spark-MLLib-RandomForest-Financiamento-Credito (1).ipynb		Cap11-Spark-MLLib-RandomForest-Financiamento-Credito (1).ipynb
Cap11-Spark-MLLib-RegLinear.ipynb		Cap11-Spark-MLLib-RegLinear.ipynb
Cap11_Caret_Machine_Learning_R (1).ipynb		Cap11_Caret_Machine_Learning_R (1).ipynb
Cap11_Classificacao_Ocorrencia_Cancer.ipynb		Cap11_Classificacao_Ocorrencia_Cancer.ipynb
Cap11_Exercicios_Machine_Learning.ipynb		Cap11_Exercicios_Machine_Learning.ipynb
Cap11_Gradient-Descent.ipynb		Cap11_Gradient-Descent.ipynb
Cap11_Machine_Learning_Model.ipynb		Cap11_Machine_Learning_Model.ipynb
Cap11_Machine_Learning_Regressão_Despesas_Medicas.ipynb		Cap11_Machine_Learning_Regressão_Despesas_Medicas.ipynb
Cap11_Template_Analise_Exploratoria_R.ipynb		Cap11_Template_Analise_Exploratoria_R.ipynb
Cap12-Arvore-Decisao-Rpart-Cluster-Kmeans.md		Cap12-Arvore-Decisao-Rpart-Cluster-Kmeans.md
Cap12-Deep-Learning-Treinamento.ipynb		Cap12-Deep-Learning-Treinamento.ipynb
Cap13_Exercicios_Modelos.ipynb		Cap13_Exercicios_Modelos.ipynb
Cap14_Analise_Credito_Classificacao.ipynb		Cap14_Analise_Credito_Classificacao.ipynb
Cap15_Sistema_Recomendacao_Filmes.ipynb		Cap15_Sistema_Recomendacao_Filmes.ipynb
Cap18_Modelo_Preditivo_Analise_Risco_Credito.ipynb		Cap18_Modelo_Preditivo_Analise_Risco_Credito.ipynb
Cerebro-Regressao.ipynb		Cerebro-Regressao.ipynb
DecisionTree-Python.ipynb		DecisionTree-Python.ipynb
Fraud_Analytics_1_Analise_Exploratoria.ipynb		Fraud_Analytics_1_Analise_Exploratoria.ipynb
Fraud_Analytics_2_Amostragem.ipynb		Fraud_Analytics_2_Amostragem.ipynb
Fraud_Analytics_3_Random_Forest.ipynb		Fraud_Analytics_3_Random_Forest.ipynb
Fraud_Analytics_4_Redes_Neurais.ipynb		Fraud_Analytics_4_Redes_Neurais.ipynb
Gradient-Boosting.ipynb		Gradient-Boosting.ipynb
Introdução_a_Machine_Learning_3.ipynb		Introdução_a_Machine_Learning_3.ipynb
Machine_Learning_Regressao.ipynb		Machine_Learning_Regressao.ipynb
Material_Referencia_Datas.ipynb		Material_Referencia_Datas.ipynb
Modelagem_Financeira_Quantmod.ipynb		Modelagem_Financeira_Quantmod.ipynb
People_Analytics_RH.ipynb		People_Analytics_RH.ipynb
Processo-Especificado-Classificacao-Machine-Learning-Parte1.ipynb		Processo-Especificado-Classificacao-Machine-Learning-Parte1.ipynb
Processo-Especificado-Regressão-Machine-Learning-Parte2.ipynb		Processo-Especificado-Regressão-Machine-Learning-Parte2.ipynb
Processo-Machine-Learning-Classificacao-Python.ipynb		Processo-Machine-Learning-Classificacao-Python.ipynb
Processo-Machine-Learning-Regressao.ipynb		Processo-Machine-Learning-Regressao.ipynb
Regressao_Linear_Etapas_Apartamento.ipynb		Regressao_Linear_Etapas_Apartamento.ipynb
Roteiro-Regressao-Linear-Consumo-Cerveja.ipynb		Roteiro-Regressao-Linear-Consumo-Cerveja.ipynb
Roteiro-Regressao-Linear-Imoveis.ipynb		Roteiro-Regressao-Linear-Imoveis.ipynb
Simulador-Interativo-IPython-Testagem-Modelos.ipynb		Simulador-Interativo-IPython-Testagem-Modelos.ipynb
Template-Algoritmos-Machine-Learning.ipynb		Template-Algoritmos-Machine-Learning.ipynb
classificacao_de_venda.ipynb		classificacao_de_venda.ipynb
classificador_filmes_kmeans.ipynb		classificador_filmes_kmeans.ipynb
ml01_bibliotecas.pdf		ml01_bibliotecas.pdf
ml02_fluxo_trabalho_machine_learning.pdf		ml02_fluxo_trabalho_machine_learning.pdf
ml04_dados_ausentes.pdf		ml04_dados_ausentes.pdf
ml05_limpeza_dados.pdf		ml05_limpeza_dados.pdf
principais_algoritmos.pdf		principais_algoritmos.pdf
xts_Series_Temporais.ipynb		xts_Series_Temporais.ipynb

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