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Description: Evaluated the performance of LSTM network to predict Google close stock price. Addressed the issue of vanishing gradient in long-term sequences using long short term memory architecture, and developed a model to predict the stock price, approximates the actual value.
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See project here
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Description: Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modelling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.
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See project here
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Description: Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Used multiple algorithms and both empirically and theoretically compared and contrasted their results. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.
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See project here
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Description: Investigated factors that affect the likelihood of charity donations being made based on real census data. Developed a naive classifier to compare testing results to. Trained and tested several supervised machine learning models on preprocessed census data to predict the likelihood of donations. Selected the best model based on accuracy, a modified F-scoring metric, and algorithm efficiency.
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See project here
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent