Cloud Academy – Getting Started With Deep Learning Working With Data Gradient Descent

Cloud Academy – Getting Started With Deep Learning Working With Data Gradient Descent-STM
English | Size: 1.98 GB
Category: Tutorial

Learn about the importance of gradient descent and backpropagation, under the umbrella of Data and Machine Learning, from Cloud Academy.

From the internals of a neural net to solving problems with neural networks to understanding how they work internally, this course expertly covers the essentials needed to succeed in machine learning.

Linkedin Learning – Deep Learning Image Recognition

Linkedin Learning – Deep Learning Image Recognition-ZH
English | Size: 307.54 MB
Category: Tutorial

Thanks to deep learning, image recognition systems have improved and are now used for everything from searching photo libraries to generating text-based descriptions of photographs. In this course, learn how to build a deep neural network that can recognize objects in photographs. Find out how to adjust state-of-the-art deep neural networks to recognize new objects, without the need to retrain the network. Explore cloud-based image recognition APIs that you can use as an alternative to building your own systems. Learn the steps involved to start building and deploying your own image recognition system

PacktPub – Master Deep Learning with TensorFlow 2.0 in Python [2019]

PacktPub – Master Deep Learning with TensorFlow 2.0 in Python [2019] [Video]
English | Size: 2.3 GB
Category: Programming | Cloud-Comp | E-learning

Build deep learning algorithms with TensorFlow 2.0, dive into neural networks, and apply your skills in a business case.

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