I require a freelancer who knows how to code in Python and one who has prior experience in creating recommender systems.
I have three files: users (information about users), items (information about items), and data (information about users and the item ratings).
The recommender system will give the users 4 recommendations, each recommendation is based on the 4 types of algorithms i.e. Content Filtering, Item-Based Collaborative Filtering, User-Based Collaborative Filtering and Hybrid Approach.
The freelancer should also evaluate these algorithms to measure the effectiveness and compare against the different approaches.
I am flexible with the way the freelancer would like to approach this; this is also a learning curve for me so someone who is able to explain the coding and process to me would be ideal.
More details can be discussed and clarified on chat.
If I find the freelancer great to work with, there will definitely be more work in future. But at the first instance this is what I require. Thank you.
Have done many such projects. Its a piece of cake for me! Will be able to complete in 3 days. Also I can suggest more techniques apart from just user-user or user-item or item-item collaborative filtering. The problem Daha Fazla
Bu iş için 10 freelancer ortalamada £73 teklif veriyor
I am a data scientist and have experience with machine learning and statistical analysis of data using R and Python. I have previously worked unsupervised machine learning algorithms and also build recommendation syste Daha Fazla
Hello, I am ready to make the recommendation system for you . I am a machine learning practitioner for last 8 yrs .Lets discuss the details on chat . Thanks a lot ........................ Himanshu Arora
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Hello, I am expert in . I have more than 7 years experience in web scrapping i have successfully completed more than 1000 projects in web scrapping. You will be glad to know that i am best fit for your task,i can d Daha Fazla
We are a company working in big data and analytics space and have delivered to multiple banks and nbfcs, also to internet companies and leading retailers in Europe and US. We can provide great insights into both collab Daha Fazla