💡 [FEATURE] - ADD DEEP LEARNING RESOURCE

Idea Contribution

[X] I have read all the feature request issues.
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Explain feature request

Deep Learning Roadmap, that involve a user or stakeholder suggesting the addition of a new fundamental concept or technique to enhance the learning experience. For example, a user might request the inclusion of a section on optimization algorithms, such as gradient descent variants, to deepen understanding in that area.

Explain your solution

In response to the feature request, the solution could involve incorporating a new module within the roadmap dedicated to optimization algorithms. This module would cover fundamental optimization techniques used in deep learning, including gradient descent, stochastic gradient descent, momentum optimization, and Adam optimization. Each technique would be explained in detail, along with its mathematical principles and practical implementations.

Any alternative approaches/features

Alternatively, instead of adding a new module specifically for optimization algorithms, the existing modules on techniques such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) could be expanded to include discussions on optimization methods commonly used with these techniques. This approach would integrate the optimization concepts seamlessly into the existing roadmap structure, providing learners with a more comprehensive understanding of how optimization algorithms relate to specific deep learning techniques.

Additional Context

Considering the rapid evolution of deep learning techniques and their widespread applications, the inclusion of optimization algorithms is essential for learners to grasp foundational concepts effectively. Furthermore, optimization plays a critical role in training deep neural networks, influencing their convergence and performance. By providing learners with a thorough understanding of optimization algorithms, they can develop the skills necessary to design and train efficient deep learning models effectively.

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