Image Recognition with Neural Networks From Scratch(FREE)

Write An Image Recognition Program in Python

4.05 (198 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Write a Python program that recognizes images from scratch without using any libraries!

Understand A Neural Network is.

Understand some important mathematical prerequisites such as functions and their computational graphs.

Understand conceptually what a derivative and a gradient is to fully appreciate the Gradient Descent Algorithm.

Understand the Gradient Descent Algorithm, the central algorithm in machine learning with Neural Networks.

Understand Backpropagation and its importance in computing gradients.

Be able to implement the full Python program in 50 lines of code that recognizes images.

Why take this course?

THIS COURSE IS NOW FREE!!

Because of my busy schedule, I will not be able to maintain or support this course. Udemy requires that video content must be under 2 hours to make a course free. So I have unpublished most of the videos to satisfy the requirements. Please see my youtube channel for all lecture videos. Youtube Channel: @longnguyen8112

Enjoy!

This is an introduction to Neural Networks. The course explains the math behind Neural Networks in the context of image recognition. By the end of the course, we will have written a program in Python that recognizes images without using any autograd libraries. The only prerequisite is some high school precalculus. Although the prerequisite is minimal, we will discuss many advanced topics including:

1) functions and their computational graphs.

2) neural networks

3) conceptually understand the derivative and the gradient.

4) gradient descent and backpropagation

5) the multivariable chain rule

6) mini-batch gradient descent

THIS COURSE IS NOW FREE!!

Enjoy!

Reviews

BiggNikk

April 24, 2021

i took something like this in university 8 years ago and didn't understand it at all. Now i do. The lecturer also does a great job of condensing all the important info from the books.

Chelaru

January 26, 2021

It was good pretty good so far. I didn't like that the teacher used some functions that he made himself instead of working with the predefined methods available in the data set. I think that would have been better.

Pranav

May 10, 2020

Interesting. The prof knows the material well and homework also helps. Nice way to implement easy machine learning concepts into programming.

Yuyu

April 22, 2020

This course is amazing so far! I'm over half way done with the course. Dr. Long delineated the content so nicely. The contents are practical, concise, and manageable. Although there is so much for me to digest, I feel like I am getting more and more each time I go over the video and by doing the homework assignments. So far, this is course has been great! I highly recommend it!

Abhinav

January 6, 2020

No, it was terrible, I expected to have a CLEAR and EASY way to follow the course. Although this person knows what they are doing, they cant teach very well. How can I create a machine learning program if he won't even share the databases with me

Shaul

September 14, 2019

Great course. Did it end to end. I liked that the math was explained and no machine learning libraries were used.

Rodrigo

June 23, 2019

Great course for those who want to understand the maths behind Neural Networks, specially Feedforward and Backpropagation.

Shruthi

June 22, 2019

i am very happy to see that i found my topic with a clear explanation and the explanation was too good

Abeer

April 16, 2019

The instructor of this course explained the fundamentals of neural nets with a great deal of mathematical detail. I liked the way he stuck to the problem and explained it in depth instead of loitering around almost all the corridors of neural networks.

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