Artificial Neural Networks and Deep Learning in Practice

人工神经网络和深度学习是机器学习中最新和最先进的主题，在许多领域都有多种应用。从计算机视觉到药物发现和股市预测，它们在许多领域都显示出可喜的成果。此外，由于其通过部署不同数据类型解决不同问题的能力和潜力，许多研究人员和非计算机科学或相关领域的人员对在他们的项目中学习和使用人工神经网络和深度学习架构感兴趣。

本课程通过一些编码示例为您提供一些人工神经网络和深度学习的基础知识，以更好地理解这些概念。本课程适合机器学习领域和深度学习的新手，并希望学习如何使用 Python、TensorFlow 和 Keras 实现深度学习算法。

该课程提供了一些参考资料和链接以供更多阅读。您可以访问问答环节来提出您的问题。您还可以通过消息系统与教授交流以提出您的问题。

我希望这门课程的内容会受到全球本科生和研究生以及深度学习研究人员的欢迎，包括学术界和工业界的从业者。

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 29 lectures (3h 48m) | Size: 1.8 GB

With Introductory Review on Machine Learning

What you’ll learn
The fundamentals of Artificial Neural Networks (ANNs) and reviews state-of-the-art DL examples.
The fundamental of Deep learning and the most popular algorithms.
It has several coding examples.
It has several quizzes for learning better.

Requirements
Probability,
Calculus,
Basic of Python, Tensor Flow, Keras, and Numpy.

Description
Artificial Neural Networks and Deep Learning are the most recent and advanced topics in machine learning, with several applications in many fields. They show promising results in many areas, from computer vision to drug discovery and stock market prediction. Also, because of its capabilities and potential in solving different problems by deploying different data types, many researchers and people who are not in computer science or related fields are interested in learning and using Artificial Neural Networks and Deep learning architectures in their projects.

This course gives you some fundamentals of artificial neural networks and deep learning with some coding examples to understand the concepts better. The course is suitable for people who are new in the machine learning field and deep learning and would like to learn how to implement deep learning algorithms using Python, TensorFlow, and Keras.

The course provides some references and links for more reading. You have access to the Q/A session for asking your question. You also have access to communicate with the professor by the messaging system to ask your questions.

I would expect this course’s contents to be welcomed worldwide by undergraduate and graduate students and researchers in deep learning, including practitioners in academia and industry.

Who this course is for
It is useful for undergraduate and graduate students, as well as practitioners in industry and academia.
Anyone who would like to learn Neural networks and deep learning.