Published 11/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.38 GB | Duration: 2h 34m
Practical Guide to Tensorflow and Keras
What you'll learn
Understand the intuition behind Artificial Neural Networks
Apply Artificial Neural Networks in practice
Understand the intuition behind Recurrent Neural Networks
Understand the intuition behind Convolution Neural Networks
Learn how to apply neural networks in several practical examples
Build model in tensorflow and keras
Requirements
Basic understanding about Python: variables, functions, OOP
A Google account (google-colab is used as the Python IDE)
Description
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. Deep learning is getting lots of attention lately and for good reason. It's achieving results that were not possible before.Deep Learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over time without being programmed to do so.In data science, an algorithm is a sequence of statistical processing steps. In machine learning, algorithms are 'trained' to find patterns and features in massive amounts of data in order to make decisions and predictions based on new data. The better the algorithm, the more accurate the decisions and predictions will become as it processes more data.Deep Learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.Google's AlphaGo program was able to beat a world...
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