In this CNN and RNN: In Depth video, you’ll learn about what convolution neural network and recurrent neural networks are. You’ll understand how CNN and RNN work along with hands-on examples about image classification and time series analysis.
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So, what is Deep Learning?
Deep learning is a subset of machine learning. It is a field that is based on learning and improving on its own by examining computer algorithms. While machine learning uses simpler concepts, deep learning works with artificial neural networks, which are designed to imitate how humans think and learn. Until recently, neural networks were limited by computing power and thus were limited in complexity. However, advancements in Big Data analytics have permitted larger, sophisticated neural networks, allowing computers to observe, learn, and react to complex situations faster than humans. Deep learning has aided image classification, language translation, speech recognition.
In recent years, AI and ML technologies have made several breakthroughs, and the rising demand for AI applications across different industries has led to the significant growth of machine learning.
As per marketsandmarkets.com, the machine learning market is expected to grow 9 billion dollars by 2022, at a cagr of 44%.
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