Essays about: "long short-term memory network"
Showing result 6 - 10 of 204 essays containing the words long short-term memory network.
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6. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE
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7. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Since many log tracing application and diagnostic commands are now available on nodes at base station, event log can easily be collected, parsed and structured for network performance analysis. In order to improve In Service Performance of customer network, a sequential machine learning model can be trained, test, and deployed on each node to learn from the past events to predict future crashes or a failure. READ MORE
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8. Plant yield prediction in indoor farming using machine learning
University essay from Högskolan i Skövde/Institutionen för informationsteknologiAbstract : Agricultural industry has started to rely more on data driven approaches to improve productivity and utilize their resources effectively. This thesis project was carried out in collaboration with Ljusgårda AB, it explores plant yield prediction using machine learning models and hyperparameter tweaking. READ MORE
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9. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis
University essay from KTH/Matematik (Avd.)Abstract : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. READ MORE
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10. Artificial Neural Networks for Financial Time Series Prediction
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. READ MORE