Deep Learning Literacy

Paths

Expanded

Deep Learning Literacy

Author: Abdul Rehman Yousaf

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... Read more

Pre-requisites

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

Beginner

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.

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Literacy Essentials: Core Concepts Deep Learning

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by Pratheerth Padman

Literacy Essentials: Core Concepts Neural Network

by Abdul Rehman Yousaf

Nov 9, 2021 / 48m

48m

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Description

Deep learning systems are capable of handling data in abundant volumes. As data is being generated at a rate that exceeds our expectations, the importance of deep learning is becoming more significant and prevailing in industries across the world. In this course, Literacy Essentials: Core Concepts Neural Network, you'll learn the basics of Artificial Neural Networks. First, you’ll explore a brief history of neural networks, specifically how they are inspired from biological neurons. Next, you’ll discover the basics of the structure of a neuron, how it connects to other neurons to form a neural network. Finally, you'll understand vectorization and how it can help us to improve the performance of neural networks. When you’re finished with this course, you’ll have the skills and knowledge of the core concepts of neural networks needed as the foundation to implement deep learning.

Table of contents
  1. Course Overview
  2. Introducing Artificial Neural Networks
  3. Understanding Neural Network’s Structure and Operations
  4. Understanding Vectorized Neural Networks

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Literacy Essentials : Core Concepts Convolutional Neural Network

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by Alex Schultz

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Literacy Essentials: Core Concepts Generative Adversarial Networks

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by Jerry Kurata

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Literacy Essentials: Core Concepts Recommender Systems

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by Rushabh Doshi

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Literacy Essentials: Core Concepts Data Normalization

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by Ifedayo Bamikole

Learning Paths

Deep Learning Literacy

  • Number of Courses6 courses
  • Duration1 hours
  • Expanded

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

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