Neural

Cloud Academy – Building Convolutional Neural Networks on Google Cloud

Cloud Academy – Building Convolutional Neural Networks on Google Cloud-STM
English | Size: 682.35 MB
Category: Tutorial

Once you know how to build and train neural networks using TensorFlow and Google Cloud Machine Learning Engine, what s next? Before long, you ll discover that prebuilt estimators and default configurations will only get you so far. To optimize your models, you may need to create your own estimators, try different techniques to reduce overfitting and use custom clusters to train your models

Packt – PyTorch Bootcamp for Artificial Neural Networks and Deep Learning Applications

Packt – PyTorch Bootcamp for Artificial Neural Networks and Deep Learning Applications
English | Size: 5.31 GB
Category: Tutorial

Key Features
A full introduction to Python Data Science and Anaconda, a powerful Python-driven data science framework
A thorough grounding in how to use PyTorch to implement common deep learning algorithms such as Convolutional Neural Networks (CNNs) on real-life data
Limited mathematical jargon. The course focuses on teaching people basic Python data science concepts and builds up to using PyTorch

Udemy – Deep Learning – Recurrent Neural Networks in Python

Udemy – Deep Learning- Recurrent Neural Networks in Python
English | Size: 1.39 GB
Category: Programming | Networking

Deep Learning: Recurrent Neural Networks in Python
What you’ll learn
Understand the simple recurrent unit (Elman unit)
Understand the GRU (gated recurrent unit)
Understand the LSTM (long short-term memory unit)
Write various recurrent networks in Theano