ELEC 4806/5806 Introduction to Deep Learning and PyTorch/TensorFlow Lab 5 Word Embeddings 1. Experiment goal: • • • Understand RNN Understand Word Embedding. Improve the performance of the model by fine-tuning the network. For this lab only use any framework from PyTorch, TensorFlow or just normal python code from scratch to demonstrate your logical understanding of the concept. 2. Introduction: Theory Problem: Write a four-page report about Glove word representation and demonstrate how and when it's used and how it is different from word2vec. Code Problem: In this lab, you will implement word embedding using glove algorithm, the example used is word2vec, use the same file Royal_data.txt. Please refer to the Natural Language Processing(NLP) modules to complete this lab. But you need to pay attention to the following: • Word2vec steps of training data • Plagiarizing code directly from other websites is not allowed. Please try to use Google Colab to complete this Lab. Without GPU, the training process may become unacceptably long. Submission requirements (all team members need to submit): 1. Please submit the .ipynb file and make sure i can easily run your code. If you use google colab, you can download the .ipynb file by clicking “File→Download→Download .ipynb". Please include the names of all team members in the file name. 2. Please submit a pdf version as well. You can use this website (https://htmtopdf.herokuapp.com/ipynbviewer/) to convert your .ipynb file to pdf. 3. Please record a video to demo your work. Especially the code problem 4. When you are recording a video, if you just read the comments you wrote in the code, or read according to a script, then you will not be able to prove that the work was done independently by you. Therefore, the lab will be judged as plagiarism.