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.ipynb_checkpoints
.ipynb_checkpoints
 
 
.vscode
.vscode
 
 
Housing_price_Predictions
Housing_price_Predictions
 
 
Neural_networks_Diabetes
Neural_networks_Diabetes
 
 
diabetes
diabetes
 
 
spam_classification
spam_classification
 
 
.DS_Store
.DS_Store
 
 
CNN.ipynb
CNN.ipynb
 
 
DL_pratice.ipynb
DL_pratice.ipynb
 
 
Decision_trees_iris.ipynb
Decision_trees_iris.ipynb
 
 
FashionMnist_CNN.ipynb
FashionMnist_CNN.ipynb
 
 
KNN.ipynb
KNN.ipynb
 
 
ML_1.ipynb
ML_1.ipynb
 
 
Matplotlib.ipynb
Matplotlib.ipynb
 
 
Mnist_CNN.ipynb
Mnist_CNN.ipynb
 
 
NN-tensorflow.ipynb
NN-tensorflow.ipynb
 
 
Pratice.ipynb
Pratice.ipynb
 
 
README.md
README.md
 
 
Scraping_withPandas.ipynb
Scraping_withPandas.ipynb
 
 
Survival.ipynb
Survival.ipynb
 
 
Tensorflow.ipynb
Tensorflow.ipynb
 
 
Titanic_dataset(outliers).ipynb
Titanic_dataset(outliers).ipynb
 
 
Titianic_DecisionTrees.ipynb
Titianic_DecisionTrees.ipynb
 
 
abalone.ipynb
abalone.ipynb
 
 
data_visualizations.ipynb
data_visualizations.ipynb
 
 
iris_dataset.ipynb
iris_dataset.ipynb
 
 
knn.csv
knn.csv
 
 
prices.csv
prices.csv
 
 
pytorch_1.ipynb
pytorch_1.ipynb
 
 
sklearn.ipynb
sklearn.ipynb
 
 
titanic_2.ipynb
titanic_2.ipynb
 
 
titanic_datasets.ipynb
titanic_datasets.ipynb
 
 
wisconsin.ipynb
wisconsin.ipynb
 
 

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My documentation in learning Machine Learning including practices from CodeSignal, Kaggle and DataCamp. It's been an insightful journey, from been a nood to a ML enginner.

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My journey in learning Machine Learning

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