recommendation-system | Movie recommendation system using Cosine | Recommender System library

I want to reproduce the results of this article on how to make your own recommendation system. Basically she starts scraping the page https://www.nosetime.com/pinpai/2-a.html in this notebook to get the names of the perfumes. I tried to do the same but I get an error 403 with requests.get(url). Then I tried to use the same solution as in this answer, a proxy, but got the same error:

For my project , i’m trying to predict the ratings that a user will give to an unseen movie, based on the ratings he gave to other movies. I’m using the movielens dataset.The Main folder, which is ml-100k contains informations about 100,000 movies.

Before processing the data, the main data (ratings data) contains user ID, movie ID, user rating from 0 to 5 and timestamps(not considered for this project).I then split the data into Training set(80%) and test data(20%) using sklearn Library.

To create the recommendation systems, the model ‘Stacked-Autoencoder’ is being used. I’m using PyTorch and the code is implemented on Google Colab. The project is based on this https://towardsdatascience.com/stacked-auto-encoder-as-a-recommendation-system-for-movie-rating-prediction-33842386338

I'm new to deep Learning and I want to compare this model(Stacked_Autoencoder) to another Deep Learning model. For Instance,I want to use Multilayer Perception(MLP). This is for research purposes. This is the code below for creating Stacked-Autoencoder model and training the model.

I'm learning R for data analysis and using this Kaggle dataset. Following the movie recommendation script works, but when I try to generalize a dplyr code by making it a function I get an error:

I've tried troubleshooting some. It looks like the code stops at the filter and mutate functions.

The following works and gives the expected output.

Im trying to launch an ml-engine jobs submit training using a cloud composer, i'm using this guide for instructions recommendation-system-tensorflow-deploy.

Im using a plugin which google created (see the implementation here)

Im trying to make it work on python version 3.5, this by changing line 206 from:

Getting below error:

SyntaxError: invalid syntax error on this line of the code -> parsed_json = kstream.map(lambda (k,v): json.loads()) arrow indicating (>k,a), link to the code is https://github.com/patilankita79/Location-based-Restaurants-Recommendation-System/blob/master/BigDataProject/Consumer.py