Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io
In this repository, you will find the solutions of all coding challenges and jupyter notebooks
This course is an accumulation of well-grounded knowledge and experience in deep learning. It provides you with the basic concepts you need in order to start working with and training various machine learning models. You will cover both basic and intermediate concepts including but not limited to: convolutional neural networks, recurrent neural networks, generative adversarial networks as well as transformers. After completing this course, you will have a comprehensive understanding of the fundamental architectural components of deep learning. Whether you’re a data and computer scientist, computer and big data engineer, solution architect, or software engineer, you will benefit from this course.
Learn Deep Learning
Neural Networks
Training Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
Autoencoders
Generative Adversarial Networks
Attention and Transformers
Graph Neural Networks
Conclusion