north0n-FI/Predicting-the-Popularity-of-Online-News

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north0n-FI/Predicting-the-Popularity-of-Online-News

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Building a model which can predict the number of online 'shares' an article will get based on a set of variables attached to it. (Python)

Twitter-moods-as-stock-price-predictors-on-Nasdaq

An attempt to predict next day's stock price movements using sentiments in tweets with cashtags. Six different ML algorithms were deployed (LogReg, KNN, SVM etc.). Main libraries used: Pandas & Numpy

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Analysing-IMDB-reviews-using-GloVe-and-LSTM

Using the IMDB data found in Keras here a few algorithms built with Keras. The source code is from Francois Chollet's book Deep learning with Python. The aim is to predict whether a review is positive or negative just by analyzing the text. Both self-created as well as pre-trained (GloVe) word embeddings are used. Finally there's a LSTM model and the accuracies of the different algorithms are compared. For the LSTM model I had to cut the data sets of 25.000 sequences by 80% to 5.000, since my laptop's CPU was not able to run the data crunching, making the model's not fully comparable.

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Star-Wars-opening-text-crawl

Mimic of Star Wars' opening title text crawl

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K-means-clustering-on-US-crime-data

Unsupervised machine learning using U.S. crime data and k-means clustering. Crime categories: murder, assault & rape in all 50 states in 1973.

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Predicting-Nordea-stock-price-using-an-LSTM-neural-network-

Using an 80/20 split in the historical data daily closing prices where predicted using a LSTM network based on data observed in the past 30 days for each prediction

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Multivariate-Regression---King-County-House-Prices

Supervised Machine Learning Using Regression Analysis

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Predicting-terrorism-in-Europe-through-Decision-Trees-and-Random-Forests

Given enough data, could we make predictions on whether a terrorist attack will be successful, or not? This analysis aims to do just that using Decision Trees and Random Forests created with scikit-learn. (Python)

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House-Prices-Advanced-Regression-Techniques

This is my contribution to a competition on kaggle.com, where you have a dataset with 79 explanatory variables describing (almost) every aspect of c. 1500 residential homes in Ames, Iowa. The aim is to predict the final price of each home.

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Sentiment-Analysis-on-Donald-Trump-s-tweets

Trump has been tweeting since December 2009, altogether more than 23000(!) tweets. Here I analyzed the last two years only, between May 2016 and April 2018, because that era covers the most active part of his presidential campaign, as well as his presidency so far.Full article available on my linkedin-page.

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