LOGiN PANeL

«    November 2026    »
MoTuWeThFrSaSu
 1
2345678
9101112131415
16171819202122
23242526272829
30 
PoLL





eBooks Tutorials Templates Plugins Scripts Applications GFX Collections SCRiPTMAFiA.ORG
LaST oN NULLeD.org
A Quiet Place Part II (2021) 1080p BluRay HEVC 10bit TrueHD7 1-LuCY 5.54 GB | 01:37:00 | mkv | 1920X1080 | 16:9 Language:English Genres: Science Fiction,Thriller,Horror iMDB info ...
ChrisPC VideoTube Downloader Pro 15.26.1114 Multilingual Portable File size: 151 MB ChrisPC VideoTube Downloader Pro is a powerful software with a friendly user interface that allows ...
ChrisPC VideoTube Downloader Pro 15.26.1114 Multilingual File size: 63.4 MB ChrisPC VideoTube Downloader Pro is a powerful software with a friendly user interface that allows ...

RSS
RSS

FRiENDS
Nulled.org Software 8TM URL Shortener Forex Trading Crypto Trading {sape_teaser}



Recommendation System & Recommendation Engine with Python

Category: Tutorials


Recommendation System & Recommendation Engine with Python
Free Download Recommendation System & Recommendation Engine with Python
Published 11/2023
Created by EDUCBA Bridging the Gap
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 40 Lectures ( 4h 59m ) | Size: 1.83 GB


Master recommendation systems with recommendation techniques and methodologies using Python
What you'll learn
Learn concepts of Recommendation Engine
Learn the techniques used by companies like Netflix to recommend movies to the customer
Be able to build a simple but functional Recommendation Engine
Learn recommending movies, books using the recommendation system.
Learn about Collaborative based filtering.
Requirements
Basics of Python
Anaconda and Python installed in pc
Description
Learn about recommendation system. Also known as recommender engines. Recommendation Engines are everywhere. Netflix, Amazon and YouTube to name a few. Then there is the Ultimate Recommendation Engine: Google. Recommendation Engines help us make choices suited to our personal tastes.Recommender systems aim to predict users' interests and recommend product items that quite likely are interesting for them. They are among the most powerful machine learning systems that online retailers implement in order to drive sales. Data required for recommender systems stems from explicit user ratings after watching a movie or listening to a song, from implicit search engine queries and purchase histories, or from other knowledge about the users themselves. The object of this course is for you to walk away with a solid understanding of the fundamentals behind the Collaborative filtering algorithm used by companies like Netflix or Amazon Prime to recommend movies to users based on the tastes of other similar users. According to Netflix, there 70% of the videos seen by recommending the videos to the user. Not only Netflix, Amazon also claims most products, they because of their recommendation system. There is a wide range of techniques to be used to build recommender engines. In this learning path, It will mostly cover all the easy to moderate kind of techniques with hands on experience.Two types of Recommendation systems are Collaborative Based and Content based filters Recommending system. You'll be excel both the methods after the completion of course. Recommendation Engines will be essential to selling anything and Big Companies are already looking on new ways to use them and for developers and marketeers who understand them. This course will give you a fundamental, conceptual understanding of how Recommendation Engines work by walking you through building a simple toy Recommendation Engine from scratch using simple math and basic python programming skills. Taking this course is an easy way to prepare for more advance study as concepts are explained in plain language and code is walked through line by line.
Who this course is for
Any professional who want to know the secrets behind the recommendation of the products
Python beginners looking for interesting projects
Homepage
https://www.udemy.com/course/recommendation-system-recommendation-engine-with-python/





DOWNLOAD LINK


No Password - Links are Interchangeable


   
   
   


Forex Trading

Crypto Trading. 20 USD Bonus after KYC




We need your support!
Make a donation to help us stay online
        
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
	
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem

Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u

USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm





 

Information

 
  Users of GUESTS are not allowed to comment this publication.