GitHub - iamcamilasilva/MachineLearning-StudyNotebooks: This is an introductory study notebook about Machine Learning witch includes basic concepts and examples using Linear Regression, Logistic Regression, NLP, SVM and others.

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This is an introductory study notebook about Machine Learning witch includes basic concepts and examples using Linear Regression, Logistic Regression, NLP, SVM and others.

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.ipynb_checkpoints		.ipynb_checkpoints
MNIST_data		MNIST_data
official/mnist/dataset.py		official/mnist/dataset.py
smsspamcollection		smsspamcollection
01-SciPy.ipynb		01-SciPy.ipynb
02-Decision Trees and Random Forest Project.ipynb		02-Decision Trees and Random Forest Project.ipynb
02-K Means Clustering Project.ipynb		02-K Means Clustering Project.ipynb
02-K Nearest Neighbors Project.ipynb		02-K Nearest Neighbors Project.ipynb
02-Linear Regression Project.ipynb		02-Linear Regression Project.ipynb
02-Logistic Regression Project.ipynb		02-Logistic Regression Project.ipynb
02-NLP Project.ipynb		02-NLP Project.ipynb
02-Support Vector Machines Project.ipynb		02-Support Vector Machines Project.ipynb
04-Tensorflow Project Exercise.ipynb		04-Tensorflow Project Exercise.ipynb
Classified Data		Classified Data
College_Data		College_Data
Decision Trees and Random Forest.ipynb		Decision Trees and Random Forest.ipynb
Ecommerce Customers		Ecommerce Customers
K Means Clustering.ipynb		K Means Clustering.ipynb
KNN.ipynb		KNN.ipynb
KNN_Project_Data		KNN_Project_Data
Linear Regression.ipynb		Linear Regression.ipynb
Logistic Regression.ipynb		Logistic Regression.ipynb
MNIST Multi-Layer Perceptron.ipynb		MNIST Multi-Layer Perceptron.ipynb
MNIST.ipynb		MNIST.ipynb
Movie_Id_Titles		Movie_Id_Titles
NLP.ipynb		NLP.ipynb
Principal Component Analysis.ipynb		Principal Component Analysis.ipynb
Recommender System.ipynb		Recommender System.ipynb
Support Vector Machines.ipynb		Support Vector Machines.ipynb
TensorFlow Basics.ipynb		TensorFlow Basics.ipynb
TensorFlow Estimator.ipynb		TensorFlow Estimator.ipynb
USA_Housing.csv		USA_Housing.csv
advertising.csv		advertising.csv
bank_note_data.csv		bank_note_data.csv
iris.csv		iris.csv
kyphosis.csv		kyphosis.csv
loan_data.csv		loan_data.csv
titanic_test.csv		titanic_test.csv
titanic_train.csv		titanic_train.csv
u.data		u.data
u.item		u.item
yelp.csv		yelp.csv

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This is an introductory study notebook about Machine Learning witch includes basic concepts and examples using Linear Regression, Logistic Regression, NLP, SVM and others.