Artificial Intelligence for beginners: Neural Networks
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 321 MB
Genre: eLearning Video | Duration: 9 lectures (1 hour, 13 mins) | Language: English
Neural Networks: Learn the basics of artificial intelligence & master the core concepts. Learn artificial intelligence
What you'll learn
Classify massive data sets
Understand the core concepts
Implement supervised and unsupervised machine learning
Predict and classify data automatically
Fine-tuning to improve the quality of results
Learn how to work with it to get better results from complex data
Real-world examples to illustrate the power of neural network models
Requirements
Desire to learn new things
Basic knowledge about data sets
Description
Artificial Intelligence is becoming progressively more relevant in today's world. The rise of Artificial intelligence has the potential to transform our future more than any other technology. By using the power of algorithms, you can develop applications which intelligently interact with the world around you, from building intelligent recommender systems to creating self-driving cars, robots and chatbots. Neural networks are a key element of artificial intelligence.
Neural networks are one of the most fascinating machine learning models and are used to solve wide range of problems in different areas of artificial intelligence and machine learning. Yet too few really understand how neural networks actually work. This course will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. The purpose of this course is to make neural networks accessible to as many students as possible.
In this course I'm going to explain the key aspects of neural networks and provide you with a foundation to get started with advanced topics. You will build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. You'll understand how to solve complex computational problems efficiently.
By the end of this course you will have a fair understanding of how you can leverage the power of artificial intelligence and how to implement neural network models in your applications. Each concept is backed by a generic and real-world problem, making you independent and able to solve any problem with neural networks. All of the content is demystified by a simple and straightforward approach.
Who this course is for:
Scientists
Everybody interested in the subject
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