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Description

Recommender Systems and Deep Learning in Python is a specialized course on recommending systems for deep learning, machine learning, data science, and AI techniques provided by Yodemi. Today, almost all online businesses use the referral system in different ways. For example, the world\’s three largest websites, Google, YouTube, and Facebook, are using the referral system to serve users and reach more audiences, and have therefore reached their current position.

This course contains valuable information that shows you how to use the referral system on different platforms. In this course, the popular news feed algorithms Reddit, Hacker News, and Google PageRank are reviewed and Bayesian suggested techniques used by major media companies are also shown. If you also have products that you sell online or if you are writing content on your website, this course will help you use the recommendation system technique on your website and expand your business.

Courses taught in this course:

  • Accurate understanding and implementation of the recommendation system for users using simple algorithms
  • Big data matrix factoring on Spark with AWS EC2 category
  • Matrix Factoring or SVD in the Numpy JavaScript Library
  • Matrix factorization in the Keras library
  • Deep neural networks, residual networks, and self-regulation in Keras
  • Boltzmann limited car at Tensorflow

Course Characteristics of Recommender Systems and Deep Learning in Python:

  • English language
  • Duration: 11 hours and 20 minutes
  • Number of courses: 83
  • Instructor: Lazy Programmer Inc
  • File format: mp4

Course headings:

Welcome
3 lectures
12:59

Simple Recommendation Systems
17 lectures
02:09:42

Collaborative Filtering
8 lectures
01:29:18

Matrix Factorization and Deep Learning
19 lectures
02:06:28

Restricted Boltzmann Machines (RBMs) for Collaborative Filtering
13 lectures
01:36:15

Big Data Matrix Factorization with Spark Cluster on AWS / EC2
6 lectures
47:10

Basics Review
5 lectures
33:43

Appendix
12 lectures
02:25:15

Prerequisites for Recommender Systems and Deep Learning in Python:

  • For earlier sections, just know some basic arithmetic
  • For advanced sections, know calculus, linear algebra, and probability for a deeper understanding
  • Be proficient in Python and the Numpy stack (see my free course)
  • For the deep learning section, know the basics of using Keras

Pictures

Recommender Systems and Deep Learning in Python

Sample movie

Installation guide

View with your favorite Player after Extract.

English subtitle

Quality: 720p

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 1 GB

Download part 4 – 754 MB

File password (s): www.downloadly.ir

Size

3.73 GB

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