Pluralsight – Deep Learning Literacy 2022-5

Pluralsight – Deep Learning Literacy 2022-5 Downloadly IRSpace

Pluralsight – Deep Learning Literacy 2022-5
Pluralsight – Deep Learning Literacy 2022-5

Deep Learning LiteracyDeep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. This path is focused on Deep Learning popular algorithms. We have pulled a series of examples to demonstrate how deep learning is embedded in our day to day lives. These are “just in time” sort of courses that reflect the journey from problem to solution. The path is curated for Data enthusiasts that are eager to learn about Deep learning and foray into Data centered roles like Data scientist. This path will contain workable solutions This path is designed to explore the application of Deep Learning in our day to day lives. This section focuses on a few essential concepts that help learn the basics of Deep Learning. You’ll explore REcommender systems , GAN’s, RNN’s and Neural Networks.

What you’ll learn

  • Deep Learning
  • Convolutional Neural Network
  • Generative Adversarial Network

Specificatoin of Deep Learning Literacy

  • Publisher : Pluralsight
  • Teacher : Pratheerth Padman
  • Language : English
  • Level : All Levels
  • Number of Course : 7
  • Duration : 6 hours and 37 minutes

Content of Deep Learning Literacy

Deep Learning Literacy

Requirements

  • Understanding of algorithms used in the path. Though it is desired but not mandatory Understanding of Deep Learning Key concepts
  • Additional Role Titles: Data Analyst, Data Engineer, Software Engineers, and Business Analyst

Pictures

Deep Learning Literacy

Sample Clip

Installation Guide

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Subtitle : English

Quality: 720p

Download Links

Download – 648 MB

File size

648 MB