What will you learn?
- Industry Applications of deep learning
- Various examples in daily life with deep learning
- Artifical Neural Network Overview
- The Neuron
- How neuron works
- Hidden layer
- Activation Function
- Loss Function
- Gradient Descent
- Stochastic Gradient Descent
- What is Perceptrons and overview
- Drop Out
- Basics and properties
- Gradient descent in once dimension
- Multivariate Gradient descent
- Gradient descent update
- Dynamic learning rate
- Steps for creating model with Keras
- Steps for creating model with TensorFlow
- Convolutional layer
- CNN Architecture
- The cross correlation operation
- Learning a kernel
- Feature map and receptive field
- Maximum pooling and average pooling
- Flattening of layer
- Fully connected layer
- Idea behind RNN
- Applications of RNN
- One Hot Encoding
- Initialize model parameter
- Gradient Clipping
- Analysis of gradient in RNN
- Backpropagation in time in details
- Deep Recurrent neural Networks
Basic understanding of Python is required.
A warm welcome to Deep learning training course.
The Deep Learning market size is estimated to be worth $18.16 billion by end of 2023. That means the market is growing at a rapid rate of 41 percent from 2018 to 2023. Deep learning is getting used in all sectors – healthcare, fintech, e-commerce. As per Glassdoor the average salary of Deep learning engineer is $136K.
This Deep Learning course is curated by industry AI experts and aligned with the need of the industry. You will master deep learning concepts and will learn popular algorithms like CNN, RCNN, RNN, LSTM, RBM. You will build models using Keras and TensorFlow frameworks and implement deep learning algorithms. This course will prepare you for a career as Deep Learning Engineer.
By the end of this course, you will get the necessary knowledge required to enhance your career as Deep learning engineer.
This course will help you boost your career in the booming Artificial Intelligence domain. So, start your AI journey today. We will see you in the course.
Who this course is for?
1. College Freshers
2. Anyone who is willing to learn Deep learning in simple and easy steps