本次美国代写是一个Pytorch推荐算法的assignment
Requirements:
Use Anaconda Python 3.7, and Pytorch to create the
StackOverFlow_Recommender.ipynb scriptl, and t
StackOverFlow_Forcaster.ipynb scriptl to implement the following:
1) Use Google Colab (https://colab.research.google.com) or
your personal computer CPU and GPU
2) The intent is to make recommendations for a user who posted
a question and got answered, and find other questions that
would you recommend to the same user based on the
provided tags and their scores. Basically, users working on
specific domain will ask similar questions and answers. If
someone interested in python related questions, we will
recommend similar/related questions in Python but not in
Java for example.
3) Implement/Execute 4 experiments for the following
recommenders:
1. Pytorch/LSTM
2. Pytorch/Collaborative Filtering
3. Pytorch /Restricted Boltzmann Machine
4) Implement/Execute 2 experiments using the following
packages to forecast the number of questions/answers for
every day, week, and month for each of the following
technologies: Docker, Kubernetes, Python, GoLang, Angular,
React:
1. Pytorch/LSTM
2. Facebook/Profit
5) Provide a comparative analysis report discussing the results
you obtain from the 6 experiments you executed.
Assignment Deliverables:
You are required to submit a SINGLE Zip file that has the following
deliverables are:
1. Your IPYNB scripts
2. All of your source code and output
3. Output report that has your assignment run saved in OUTPUT.pdf