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Deep Learning with Keras and Tensorflow

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Keras and Tensorflow Online Training

This course from QTSInfo in which the in depth concepts of Tensorflow and Keras will be taught to you. This is a course in which all the concepts of Deep Learning framework will be covered. The Deep Learning with Keras and Tensorflow course has been developed by our expert trainers and they will teach you all the concepts with practical examples. The course will establish you as a deep learning researcher, data scientist, deep learning engineer, and many other types of Deep Learning Jobs.

Course Overview

This course in which our instructors will make you familiar with different fundamental concepts like artificial neural network, PyTorch autoencoders, and many other concepts. We will also provide you different projects and practical sessions so that you can understand all the concepts deeply. A Keras and Tensorflow tutorial will be available to you in which you will learn about different concepts of Tensorflow along with Keras.

Keras and Tensorflow Certification Key features

  • Learn how to use Keras python

  • Learn the differences between Keras and Tensorflow

  • Get the facilities of mock interview and mock test sessions

  • Demo classes will be provided free of cost

  • Get training material re4lated to Tensorflow Keras

  • Get the answer of all your queries any time

Who should take Keras vs Tensorflow

The course will be beneficial for the following people

  • People who want to develop data science applications through Keras and Tensorflow

  • People who want to learn Python concepts and use it in data science application development

  • People who want to use neural network in data science through Keras and Tensorflow

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Course curriculum / Syllabus

AI And Deep Learning Introduction
  • What is AI and Deep Learning?
  • Brief History of AI
  • Concept of UL, SL, and RL
  • Deep Learning: Successes Last Decade
  • Applications of Deep Learning
  • Challenges of Deep Learning
  • Deep Learning Project complete cycle
Artificial Neural Network
  • Perceptron Shallow Neural Network Vs Biological Neuron
  • Backpropagation
  • Role of Activation Functions and Backpropagation
  • Optimization
  • Regularization
  • Dropout layer
Neural Network and Tools
  • Applications of Deep Neural Network
  • Designing a Deep Neural Network
  • How to Choose Your Loss Function?
  • Tools for Deep Learning Models
  • Keras and its Elements
  • TFlearn Pytorch and its Elements
Deep Neural Net Optimization, Tuning, Interpretability
  • Optimization Algorithms
  • Momentum, SGD, Adagrad, NAG,  RMSprop, Adadelta, Adam
  • Concept of Width vs Depth
Convolutional Neural Net
  • Success and History
  • CNN Network Design and Architecture
  • Deep Convolutional Models
Recurrent Neural Networks
  • Sequence Data
  • Sense of Time
  • RNN Introduction
  • LSTM (Retail Sales Dataset Kaggle)
  • Concept of GRUs (Gated Recurrent Units)
  • Comparison of LSTM and GRUs
Autoencoders
  • Introduction to Autoencoders
  • Applications of Autoencoders
  • Autoencoder for Anomaly Detection

Deep Learning with Keras and Tensorflow FAQ’s:

1.What is Keras?

Keras is a deep learning framework and professionals can perform different types of experiments. It works at a fast speed and it can help you to go ahead of your competitors.

2.What is Tensorflow?

Tensorflow is an open-source library which can be used easily in Python. The library consists of different functions which help in numerical calculation.

3.What is Tensorflow used for?

Tensorflow can be used for developing text based applications, image recognition, voice recognition, and other things

4.Will I get the facility of demo class?

Yes! We will provide the facility of demo class

5.Will you develop our professional resume?

Yes! We will develop your professional resume.

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Why QTS INFO

Best Virtual training classrooms for IT aspirants

Real time curriculum with job oriented training.

Around the clock assistance

We are eager to solve your queries 24*7 with help of our expert faculty.

Flexible Timings

Choose your schedule as per your convenience. No need to delay your work

Mock projects

Real world project samples for practical sessions

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