graphlab

University of Washington

Machine learning boiler plate to get you started in minutes (graphlab + sframe + jupyter + docker)

My Assignments of Coursera Machine Learning Specialization using Scikit-Learn, Pandas, Numpy and Scipy

Collaborative filtering project

MIT xPRO Data Science Course Movie Recommendations Case Study

Recommendation System for points of interests

This repository contains all notes and assignments of coursera Machine Learning Specialization created by University of Washington

Machine Learning - University of Washington

Machine Learning applications done using Ipython Notebooks

A novel hotel review sentiment analysis method with a high F1 score (0.97) based on logistic classification

Recommendation system for Movie ratings dataset using Collaborative Filtering with different models

Deep Learning Projects written in Python with TensorFlow and Keras

Ridge Regression for House details dataset with Turicreate (GraphLab)

tour product recommendation system with k-nn model

Taking the course with numpy, pandas and scikit-learn instead of TuriCreate and Graphlab. Totally recommendable.

Distributed Graphs Processing with Apache Spark

Machine Learning Specialization work from UW on Coursera

NATKERNEL — Universal Grammar Kernel. N=7 ∈ [4,12]. Designed by law. Autonomous kernel engineering system with SAI. Author: Josué Argaña Silguero.

Distributed implementation of dag-nmf in Graphlab (CMU version).