Machine-Learning-with-Python

Repository of my Machine Learning Implementations in Python. Collated learning from Coursera, Dato and other Python Tutorials.

Machine Learning Foundations: A Case Study Approach - is part I of the Machine Learning Specialization course in Coursera. It provides an introductory overview of Regression, Classification, Clustering and Similarity, Recommending Products and Deep Learning. Primarily it uses GraphLab Create ML framework to analyse use cases.

Name		Name	Last commit message	Last commit date
Latest commit History 42 Commits
Coursera-Machine-Learning-Classification		Coursera-Machine-Learning-Classification
Coursera-Machine-Learning-Clustering-And-Retrieval		Coursera-Machine-Learning-Clustering-And-Retrieval
Coursera-Machine-Learning-Foundations		Coursera-Machine-Learning-Foundations
Coursera-Machine-Learning-Regression		Coursera-Machine-Learning-Regression
Homesite		Homesite
Prudential		Prudential
.gitattributes		.gitattributes
.gitignore		.gitignore
DM-ST3-1.ipynb		DM-ST3-1.ipynb
DM-ST3-2.ipynb		DM-ST3-2.ipynb
DM-ST3-3.ipynb		DM-ST3-3.ipynb
ML-CSCE-685-Clustering-Evaluation.ipynb		ML-CSCE-685-Clustering-Evaluation.ipynb
ML-CSCE-685-Decision-Trees.ipynb		ML-CSCE-685-Decision-Trees.ipynb
ML-CSCE-685-GaussianNB-Pima-Indians-Diabetes.ipynb		ML-CSCE-685-GaussianNB-Pima-Indians-Diabetes.ipynb
ML-CSCE-685-Introduction.ipynb		ML-CSCE-685-Introduction.ipynb
ML-CSCE-685-K-Nearest-Neighbors.ipynb		ML-CSCE-685-K-Nearest-Neighbors.ipynb
ML-CSCE-685-KMeans-Agglomerative-DBSCAN.ipynb		ML-CSCE-685-KMeans-Agglomerative-DBSCAN.ipynb
ML-CSCE-685-Linear-Regression-Regularization.ipynb		ML-CSCE-685-Linear-Regression-Regularization.ipynb
ML-CSCE-685-Linear-Regression.ipynb		ML-CSCE-685-Linear-Regression.ipynb
ML-CSCE-685-Logistic-Regression.ipynb		ML-CSCE-685-Logistic-Regression.ipynb
ML-CSCE-685-MNIST-Evaluation-of-Classifiers.ipynb		ML-CSCE-685-MNIST-Evaluation-of-Classifiers.ipynb
ML-CSCE-685-NaiveBayes-Spam-Classification.ipynb		ML-CSCE-685-NaiveBayes-Spam-Classification.ipynb
ML-CSCE-685-Neural-Networks-With-Keras.ipynb		ML-CSCE-685-Neural-Networks-With-Keras.ipynb
ML-CSCE-685-Performance-Comparison-of-Ensemble-Learning-On-Different-UCI-ML-Datasets.ipynb		ML-CSCE-685-Performance-Comparison-of-Ensemble-Learning-On-Different-UCI-ML-Datasets.ipynb
ML-CSCE-685-Understanding-Validation-And-Learning-Curves.ipynb		ML-CSCE-685-Understanding-Validation-And-Learning-Curves.ipynb
README.md		README.md
UMICH SI650-Sentiment Classification.ipynb		UMICH SI650-Sentiment Classification.ipynb
UMICH-SI650-Sentiment-Classification.ipynb		UMICH-SI650-Sentiment-Classification.ipynb
UMICH_SI650_test_data.txt		UMICH_SI650_test_data.txt
UMICH_SI650_train_data.txt		UMICH_SI650_train_data.txt
blend.py		blend.py
lending-club-data.gl.zip		lending-club-data.gl.zip
xgb_stacker_starter.py		xgb_stacker_starter.py

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