dummy-ilh / graphlab

* See all my Machine Leaning projects ! : Adaboost ensemble, Latent Dirichlet Allocation, Decision tree, Kmean, Logistic Regression, Latent Dirichlet Allocation , TF-IDF, Clustering, Image classification, Sentiment analysis, Recommendation, Gaussian Mixture Model, Nearest neighbors.

My projects in this repository are implemented based on glaphlab Framework.

* Adaboost ensemble, Latent Dirichlet Allocation, Decision tree, Kmean, Logistic Regression, Latent Dirichlet Allocation

* TF-IDF, Clusteing, Image classification, Sentiment analysis, Recommendation, Gaussian Mixture Model, Nearest neighbors.

[Adaboost ensembling_case study lending club_Explore the robustness of Adaboost to overfitting](Adaboost ensembling_case study lending club_Explore the robustness of Adaboost to overfitting..ipynb)

[Deep Features for Image Retrieval](Deep Features for Image Retrieval.ipynb)

[Ensemble Method_case study lending club-boosting](Ensemble Method_case study lending club-boosting.ipynb)

[Image Classification using Deep Features](Image Classification using Deep Features .ipynb)

[Image Retrieval using deep features.ipynb](Image Retrieval using deep features.ipynb)

[Latent Dirichlet Allocation_Text data Processing](Latent Dirichlet Allocation_Text data Processing.ipynb)

[Logistic Regression via Stochastic Gradient Ascen_online-learning_sentment analysis.ipynb](Logistic Regression via Stochastic Gradient Ascen_online-learning_sentment analysis.ipynb)

[Logistic Regression with L2 regularization_linear-classifier.ipynb](Logistic Regression with L2 regularization_linear-classifier.ipynb)

[Predicting sentiment-linear-classifier.ipynb](Predicting sentiment-linear-classifier.ipynb)

[Song recommender](Song recommender_quiz_myver.ipynb)

[TF IDF_Document retrieval_wikipedia.ipynb](TF IDF_Document retrieval_wikipedia.ipynb)

[Clustering with kmeans_hierarchical clustering_Wiki data](Clustering with kmeans_hierarchical clustering_Wiki data.ipynb)

[binary decision trees_lending club](binary decision trees_lending club.ipynb)

[binary decision trees2_lending club](binary decision trees2_lending club.ipynb)

[decision-tree_lending club case study- preventing overfitting](decision-tree_lending club case study- preventing overfitting.ipynb)

document-retrieval

[gaussian mixture model_Expectation Maximization](gaussian mixture model_Expectation Maximization.ipynb)

[k-means_Clustering Wikipedia documents](k-means_Clustering Wikipedia documents.ipynb)

[logistic regression_Analyzing_predicting_ product sentiment from product reviewb](logistic regression_Analyzing_predicting_ product sentiment from product review.ipynb)

[logistic regression_linear-classifier_log likelyhood_gradient ascent_sentment analysis](logistic regression_linear-classifier_log likelyhood_gradient ascent_sentment analysis.ipynb)

[nearest-neighbors-Locality Sensitive Hashing_Wikipedia](nearest-neighbors-Locality Sensitive Hashing_Wikipedia.ipynb)

[nearest-neighbors-finding similar documents in Wikipedia, news articles, StackOverflow](nearest-neighbors-finding similar documents in Wikipedia, news articles, StackOverflow.ipynb)

[precision-recall_logistic regression_amazon sales data](precision-recall_logistic regression_amazon sales data.ipynb)

[text-data processing_Gaussian Mixture Model](text-data processing_Gaussian Mixture Model.ipynb)