×
MindLuster Logo

How to Build Neural Network in Pytorch PyTorch Tutorial for Beginners Simplilearn

Share your inquiries now with community members Click Here
Sign Up and Get Free Certificate
Sign up Now
Lesson extensions

Lessons List | 20 Lesson

Comments

Our New Certified Courses Will Reach You in Our Telegram Channel
Join Our Telegram Channels to Get Best Free Courses

Join Now

We Appreciate Your Feedback

Excellent
2 Reviews
Good
0 Reviews
medium
0 Reviews
Acceptable
0 Reviews
Not Good
0 Reviews
4.6
13 Reviews

Harshita Bisht

GOOD COURSE
2025-11-09

Anjali Negi

Great
2025-11-09

ERWIN PINEDA

Thank You
2025-10-19

Jeffrey Ayson

thank you very much, i learn a lot
2025-10-09

Edson Matessane

It has been nice to be joining you and study all those amazing lessons. please keep it up.
2025-06-18

Gaurav Kumar Singh

good
2025-05-22

Ravi Kumar

Very interesting course
2025-04-29

Anurag Gautam

very nice
2025-04-19

Pritmanyu Kumar

Good
2025-04-19

sangam kumar

Nyce
2025-04-17

Saina Mishra

Nice learning platform
2025-04-17

Sonam kumari

type of machine learning algorithm inspired by the human brain, designed to recognize patterns and make predictions. It's a network of interconnected nodes (artificial neurons) that learn from data to make decisions. Neural networks are used in various applications like image recognition, natural language processing, and predictive modeling. 
Here's a more
2025-04-15

Show More Reviews

Course Description

Neural network in machine learning course, in this course we delve into the intricate workings of neural networks, a fundamental concept in machine learning. From understanding the basic architecture to exploring advanced techniques, this course covers it all. Through a combination of theoretical explanations and practical hands-on exercises, you'll gain insight into how neural networks mimic the human brain's computational process. We'll cover topics such as perceptrons, activation functions, feedforward and backpropagation algorithms, as well as various types of neural networks like convolutional neural networks (CNNs) and recurrent neural networks (RNNs). By the end of this course, you'll have a solid understanding of neural networks and be equipped with the knowledge to apply them to solve real-world problems in machine learning. Join us as we unravel the mysteries of neural networks and unleash their potential in the field of machine learning.