This Deep Learning full course covers all the concepts and techniques that will help you become an expert in Deep Learning. First, you will learn the basics of Deep Learning and understand how to install TensorFlow, what is TensorFlow, TensorFlow Object detection API works, different Deep Learning frameworks, convolutional neural networks, recurrent neural networks in Python, Deep Learning applications and look at the essential interview questions.

Below topics are explained in this Deep Learning full course video:
Deep Learning Course 0:00
1.Deep Learning: 02:13
2.Working of neural networks: 02:25
3.Horus Technology: 06:10
4.What is Deep Learning?: 06:50
5.Image Recognition: 07:00
6.Why do we need Deep Learning?: 10:20
7.Applications of Deep Learning: 11:40
8.What is a Neural Network?: 18:10
9.Biological Neuron vs Artificial Neuron: 21:20
10.Why are Deep Neural Nets hard to train?: 39:10
11.Neural Network Prediction: 42:00
12.Top Deep Learning Libraries: 1:12:50
13.Why TensorFlow?: 1:14:00
14.What is TensorFlow?: 1:16:10
15.What are Tensors?: 1:17:30
16.What is a Data Flow graph?: 1:20:20
17.Program Elements in TensorFlow: 1:22:50
18.TensorFlow program basics: 1:29:40
19.Use case Implementation using TensorFlow: 2:01:16
20.TensorFlow Object Detection: 2:20:46
21.COCO Dataset: 2:21:56
22.TensorFlow Object Detection API Tutorial: 2:31:46
23.Deep Learning Frameworks: 2:42:26
24.Keras: 2:45:16
25.PyTorch: 2:47:26
26.How image recognition works?: 3:18:16
27.How CNN recognizes images?: 3:26:06
28.Types of Recurrent Neural Network: 4:29:13
29.Working of LSTMs: 4:37:53
30.Deep Learning Applications: 5:16.21

What is Deep Learning?
Deep learning can be considered as 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.

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