SKILL PATH
Neural Networks: Beginners to Advanced
This path is for beginners learning neural networks for the first time. It starts with basic concepts and moves toward advanced topics with practical examples. This path is one of the best options for learning neural networks. It has many examples of image classification and identification using MNIST datasets. We will use different libraries such as NumPy, Keras, and PyTorch in our modules. This path enables us to implement neural networks, GAN, CNN, GNN, RNN, SqueezeNet, and ResNet.
60 hours
329 Lessons
Learning Objectives
Learn about neural networks from theory to practical implementation.
Learn about different types of neural networks.
Learn different aspects of deep learning.
Learn to implement GAN.
Learn to train models on different MNIST datasets with Keras and PyTorch.
Path Content
Your method is simple, straight to the point and I can practice with it everywhere, even from my phone, that's something I have never had in other learning platforms.
I highly recommend Educative. The courses are well organized and easy to understand.
I prefer Educative courses because they have a nice mix of text & images. I find that with full video courses, it can often be too easy to go into passive learning mode.
I prefer Educative courses because they have a nice mix of text & images. I find that with full video courses, it can often be too easy to go into passive learning mode.
Your method is simple, straight to the point and I can practice with it everywhere, even from my phone, that's something I have never had in other learning platforms.
I highly recommend Educative. The courses are well organized and easy to understand.
I prefer Educative courses because they have a nice mix of text & images. I find that with full video courses, it can often be too easy to go into passive learning mode.
