Neural Networks Made Easy

Learners: 2

Instructor: Ben Gorman

Duration: 2.00

This course will teach you the fundamentals of neural networks, from motivation and explanation of perceptrons to deriving and coding a multiclass neural network with stochastic gradient descent. You'll learn how to recognize hand-written digits from the MNIST dataset and understand neural networks so well that learning TensorFlow and PyTorch will be a breeze. Prerequisites include Python, NumPy, Pandas, and a good bit of calculus. Challenges and coding exercises are included. ▼▲

Course Feature Course Overview Pros & Cons Course Provider Discussion and Reviews

Go to class

Course Feature

Cost:

Free

Provider:

Udemy

Certificate:

Paid Certification

Language:

English

Start Date:

On-Demand

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 25th, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)

So easy, your dog could learn them!

What you'll learn:

Neural Network Fundamentals

Wanna understand deep learning and neural networks so well, you could code them from scratch? In this course, we'll do exactly that.
The course starts by motivating and explaining perceptrons, and then gradually works its way toward deriving and coding a multiclass neural network with stochastic gradient descent that can recognize hand-written digits from the famous MNIST dataset.
Course Goals
This course is all about understanding the fundamentals of neural networks. So, it does not discuss TensorFlow, PyTorch, or any other neural network libraries. However, by the end of this course, you should understand neural networks so well that learning TensorFlow and PyTorch should be a breeze!
Challenges
In this course, I present a number of coding challenges inside the video lectures. The general approach is, we'll discuss an idea and the theory behind it, and then you're challenged to implement the idea / algorithm in Python. I'll discuss my solution to every challenge, and my code is readily available on github.
Prerequisites
In this course, we'll be using Python, NumPy, Pandas, and good bit of calculus. ..but don't let the math scare you. I explain everything in great detail with examples and visuals.
If you're rusty on your NumPy or Pandas, check out my free courses Python NumPy For Your Grandma and Python Pandas For Your Grandpa.

Pros & Cons

Pros Cons

Free
Explains things well
Clear description

No hands on experience
Limited topics covered
No advanced topics discussed

Course Provider

Provider Udemy's Stats at AZClass

At the 2023 EdTech Breakthrough Awards program, Udemy got 'Ongoing Education Solution Provider of the Year' award.
Stack Overflow's Developer Survey ranks Udemy as the most popular platform for learning programming for two consecutive years (as of 2023)
Udemy and its certificates are acknowledged by lots of employers.
AZ Class hope that this free Udemy course can help your Neural Networks skills no matter in career or in further education. Even if you are only slightly interested, you can take Neural Networks Made Easy course with confidence!