Deep Learning Training by Experts
Our Training Process

Deep Learning - Syllabus, Fees & Duration
MODULE 1
- Introduction to Tensor Flow
 - Computational Graph
 - Key highlights
 - Creating a Graph
 - Regression example
 - Gradient Descent
 - TensorBoard
 - Modularity
 - Sharing Variables
 - Keras Perceptrons
 - What is a Perceptron?
 - XOR Gate
 
MODULE 2
- Activation Functions
 - Sigmoid
 - ReLU
 - Hyperbolic Fns, Softmax Artificial Neural Networks
 - Introduction
 - Perceptron Training Rule
 - Gradient Descent Rule
 
MODULE 3
- Gradient Descent and Backpropagation
 - Gradient Descent
 - Stochastic Gradient Descent
 - Backpropagation
 - Some problems in ANN Optimization and Regularization
 - Overfitting and Capacity
 - Cross-Validation
 - Feature Selection
 - Regularization
 - Hyperparameters
 
MODULE 4
- Introduction to Convolutional Neural Networks
 - Introduction to CNNs
 - Kernel filter
 - Principles behind CNNs
 - Multiple Filters
 - CNN applications Introduction to Recurrent Neural Networks
 - Introduction to RNNs
 - Unfolded RNNs
 - Seq2Seq RNNs
 - LSTM
 - RNN applications
 
MODULE 5
- Deep learning applications
 - Image Processing
 - Natural Language Processing
 - Speech Recognition
 - Video Analytics
 
This syllabus is not final and can be customized as per needs/updates
			
													
												
							

								
							
			
Participants in the deep learning course should have a thorough understanding of the principles of programming, as well as a solid understanding of the fundamentals of statistics and mathematics, as well as a clear grip on the critical knowledge portions of machine learning.  Deep learning algorithms are employed in a variety of industries, from automated driving to medical gadgets.  Companies like to hire people who have completed this deep learning course.  Deep learning powers a variety of AI (artificial intelligence) services and applications that automate and perform physical operations without the need for human participation.  Python is the language of deep learning.  Deep learning models in the real world could be used for driverless cars, money filtration, virtual assistants, facial recognition, and other applications. 
Because there is a strong demand for skilled deep learning engineers in various fields, this deep learning course in Mahboula certification training is ideal for intermediate and advanced experts. 
Deep learning is a subset of machine learning (ML), which is essentially a three-layer neural network. 
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Rather than being numerical, the majority of the data is in an unstructured format, such as audio, image, text, and video.