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Neural network fundamentals and deep learning

Track :

Computer Science

Lessons no : 4

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What will you learn in this course?
  • Design and implement neural network architectures for image recognition and natural language processing tasks effectively
  • Apply activation functions and perceptrons to build and optimize neural networks for real-world applications
  • Explain backpropagation and training processes to improve neural network performance and accuracy
  • Evaluate neural network models using practical techniques for better performance in deep learning projects

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Lessons | 4


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17 Reviews

S SHASHIDHAR

Good
2026-05-03

Yashashree Kadam

Helpful coarse
2026-04-24

Nitisha Kapadiya

really good
2026-04-23

VAGAVATH KHANIJA SRI

GOOD
2026-04-17

ANAPURAM ABHINAYA SRI

good
2026-04-17

Ebaa Mubarak

good
2026-04-12

Swaralee

nice course
2026-04-12

Sanjana Pandey

nice course, easy to understand
2026-04-12

BOINAPELLY SINDHUJA

good
2026-04-11

Rayan Zia

.
2026-04-07

BANDLA PRANAVI

Exceelent
2026-04-05

LUNAVATH SRILATHA

good
2026-04-04

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Neural network fundamentals course, in this course we will learn about the basics of neural networks, covering topics such as perceptrons, activation functions, backpropagation, and network architectures. You'll gain an understanding of how neural networks function and their applications in various fields like image recognition, natural language processing, and more. Through hands-on exercises and practical examples, you'll develop the skills needed to design and train neural networks effectively.