Essays about: "Machine Learning"

Showing result 1 - 5 of 602 essays containing the words Machine Learning.

  1. 1. Machine Learning to Uncover Correlations Between Software Code Changes and Test Results

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

    Author : Negar Fazeli; [2017-12-05]
    Keywords : ;

    Abstract : Statistics show that many large software companies, particularly those dealing with large-scale legacy systems, ultimately face an ever-growing code base. As the product grows, it becomes increasingly difficult to adequately test new changes in the code and maintain quality at a low cost without running a large number oftest cases [1, 2, 3]. READ MORE

  2. 2. CORPORATE BANKRUPTCY PREDICTION USING MACHINE LEARNING TECHNIQUES

    University essay from Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Author : Björn Mattsson; Olof Steinert; [2017-11-06]
    Keywords : ;

    Abstract : Estimating the risk of corporate bankruptcies is of large importance to creditors and in- vestors. For this reason bankruptcy prediction constitutes an important area of research. In recent years artificial intelligence and machine learning methods have achieved promising results in corporate bankruptcy prediction settings. READ MORE

  3. 3. COMBATING DISINFORMATION : Detecting fake news with linguistic models and classification algorithms

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC); KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Mikael Svärd; Philip Rumman; [2017]
    Keywords : fake news; machine learning; naive bayes;

    Abstract : The purpose of this study is to examine the possibility of accurately distinguishing fabricated news from authentic news stories using Naive Bayes classification algorithms. This involves a comparative study of two different machine learning classification algorithms. READ MORE

  4. 4. Prediction of securities' behavior using a multi-level artificial neural network with extra inputs between layers

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC); KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Eric Törnqvist; Xing Guan; [2017]
    Keywords : high frequency; neural network; computer science; stock market; finance; fintech; machine learning; yield; prediction; forecast; deep neural network; algo trading; financial instruments; correlation;

    Abstract : This paper discusses the possibilities of predicting changes in stock pricing at a high frequency applying a multi-level neural network without the use of recurrent neurons or any other time series analysis, as suggested in a paper byChen et al. [2017]. The paper tries to adapt the model presented in a paper by Chen et al. READ MORE

  5. 5. Deep Neural Networks for Context Aware Personalized Music Recommendation : A Vector of Curation

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Oktay Bahceci; [2017]
    Keywords : Information Filtering; Information Retrieval; Search Engine; Search Engines; Recommendation; Music Recommendation; Personalized Recommendation; Personalised Recommendation; Context Aware Recommendation; Recommender Systems; Statistical Learning; Artificial Intelligence; Machine Learning; Deep Learning; Neural Networks; Artificial Neural Networks; Feed Forward Neural Networks; Convolutional Neural Networks; Recurrent Neural Networks; Deep Neural Networks; Embedding;

    Abstract : Information Filtering and Recommender Systems have been used and has been implemented in various ways from various entities since the dawn of the Internet, and state-of-the-art approaches rely on Machine Learning and Deep Learning in order to create accurate and personalized recommendations for users in a given context. These models require big amounts of data with a variety of features such as time, location and user data in order to find correlations and patterns that other classical models such as matrix factorization and collaborative filtering cannot. READ MORE