Deployment of sentiment analysis model using Amazon sagemaker
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Updated
Feb 2, 2020 - Jupyter Notebook
Deployment of sentiment analysis model using Amazon sagemaker
Computer Vision Nanodegree second project, generating image captions. We take a prebuilt Resnet CNN model to encode the image and captions, use the RNN with LSTM to train and decode images and predict captions
Udacity - Computer Vision Nanodegree - Project 2: Image Captioning
predicting country of origin from names
RAF: A RNN-based Chatbot Development Tool
基于pytorch的RNN、LSTM模型构建,RNN进行MNIST数据集分类,LSTM进行古诗生成
Neural Networks for Neuroscience Tasks
This is the 3rd project of the Deep Learning Nanodegree.
My solution to the Udacity project of training all Seinfeld Scripts in an RNN to predict a new script based on which character talks first
2018-2019 Semester2 at Soton, lab practice for Deep Learning
Predict whether the number of confirmed people will increase or not with the use of RNN.
Retrieved financial institutions data using Twitter’s API, created a database, and performed pre-processing of this data • Created an AI module which classified each tweet into three different sentiment groups: Positive, Negative and Neutral Developed a POC which predicted the stock price of these financial institutions based on the different se…
A fully playable snake game application that features an intelligent agent trained using Deep Recurrent Q-Learning
RNN-based generator of Polish-like words
The main task of the character-level language model is to predict the next character given all previous characters in a sequence of data, i.e. generates text character by character.
Pun Detection and Interpretation: a RNN with LSTM cell approach
AI masterthesis. Iterative learning. Meta learning. Stochastic approach to adaptive computation
Research code used to study learning dynamics of RNN language models
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