AI & Deep Learning with TensorFlow

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Certs Learning
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Artificial Intelligence

About Deep Learning in TensorFlow with Python Certification Training

In this Deep Learning in TensorFlow with Python Training we will learn about what is AI, explore  neural networks, understand deep learning frameworks, implement various machine learning algorithms using Deep Networks. We will also explore how different layers in neural networks does data abstraction and feature extraction using Deep Learning.

Certs Learning’s Deep Learning in TensorFlow training is designed to make you a Data Scientist by providing you rich hands-on training on Deep Learning in TensorFlow with Python. This course is a stepping stone in your Data Science journey using which you will get the opportunity to work on various Deep Learning projects.

What are the objectives of our Deep Learning In TensorFlow with Python Course?

Deep Learning in TensorFlow with Python Training is designed by industry experts to make you a Certified Deep Learning Engineer. The Deep Learning in TensorFlow course offers:

  • In-depth knowledge of Deep Neural Networks
  • Comprehensive knowledge of various Neural Network architectures such as Convolutional Neural Network, Recurrent Neural Network, Autoencoders
  • Implementation of Collaborative Filtering with RBM
  • The exposure to real-life industry-based projects which will be executed using TensorFlow library
  • Rigorous involvement of an SME throughout the AI & Deep Learning Training to learn industry standards and best practices

Why Should you go for Deep Learning in TensorFlow with Python Certification Training?

Deep Learning is one of the most accelerating and promising fields, among all the technologies available in the IT market today. To become an expert in this technology, you need a structured training with the latest skills as per current industry requirements and best practices.

Besides strong theoretical understanding, you will be working on various real-life data projects using different neural network architectures as a part of solution strategy.

Additionally, you will receive guidance from a Deep Learning expert who is currently working in the industry on real-life projects.

What are the skills that you will be learning with our Deep Learning in TensorFlow Certification Training?

Deep Learning in TensorFlow with Python Training will help you to become a Deep Learning Engineer. It will hone your skills by offering you comprehensive knowledge on Deep Learning in TensorFlow. It will also acquaint you with the required hands-on experience for solving real-time industry-based Deep Learning projects. During this course you will be trained by our expert instructors on:

  • Deep Learning and TensorFlow Concepts
  • Working with Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN)
  • Proficiency in Long short-term memory (LSTM)
  • Implementing Keras, TFlearn, Autoencoders
  • Implementing Restricted Boltz-mann Machine (RBM)
  • Knowledge of Neural Networks & Natural Language Processing (NLP)
  • Using Python with TensorFlow Libraries
  • Perform Text Analytics
  • Perform Text Processing

Who should go for this Deep Learning in TensorFlow with Python Course?

The TensorFlow with Python Training is for all the professionals who are passionate about Deep Learning and want to go ahead and make their career as a Deep Learning Engineer. It is best suited for individuals who are:

  • Developers aspiring to be a ‘Data Scientist’
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Deep Learning (ML) Techniques
  • Information Architects who want to gain expertise in Predictive Analytics
  • Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused on one industry or skill set, it can be used by anyone to enhance their portfolio.

What are the pre-requisites for this Deep Learning in TensorFlow with Python Course?

Required Pre-requisites

    • Basic programming knowledge in Python
    • Concepts about Machine Learning

Certs Learning offers you complimentary self-paced courses:

  • Statistics and Machine learning algorithms
  • Python Essentials
1
Introduction to Deep Learning

Learning Objectives:

In this module, you’ll get an introduction to Deep Learning and understand how Deep Learning solves problems which Machine Learning cannot. Understand fundamentals of Machine Learning and relevant topics of Linear Algebra and Statistics.

 Topics:

  • Deep Learning: A revolution in Artificial Intelligence
  • Limitations of Machine Learning
  • What is Deep Learning?
  • Advantage of Deep Learning over Machine learning
  • 3 Reasons to go for Deep Learning
  • Real-Life use cases of Deep Learning
  • Review of Machine Learning: Regression, Classification, Clustering, Reinforcement Learning, Underfitting and Overfitting, Optimization

Hands-On

  • Implementing a Linear Regression model for predicting house prices from Boston dataset
  • Implementing a Logistic Regression model for classifying Customers based on a Automobile purchase dataset
2
Understanding Neural Networks with TensorFlow
3
Deep dive into Neural Networks with TensorFlow

Learning Objectives:

In this module, you’ll understand backpropagation algorithm which is used for training Deep Networks. You will know how Deep Learning uses neural network and backpropagation to solve the problems that Machine Learning cannot.

Topics:

  • Understand limitations of a Single Perceptron
  • Understand Neural Networks in Detail
  • Illustrate Multi-Layer Perceptron
  • Backpropagation – Learning Algorithm
  • Understand Backpropagation – Using Neural Network Example
  • MLP Digit-Classifier using TensorFlow
  • TensorBoard

Hands-On

  • Building a multi-layered perceptron for classification of Hand-written digits
4
Master Deep Networks

Learning Objectives:

In this module, you’ll get started with the TensorFlow framework. You will understand how it works, its various data types & functionalities. In addition, you will create an image classification model

Topics:

  • Why Deep Networks
  • Why Deep Networks give better accuracy?
  • Use-Case Implementation on SONAR dataset
  • Understand How Deep Network Works?
  • How Backpropagation Works?
  • Illustrate Forward pass, Backward pass
  • Different variants of Gradient Descent
  • Types of Deep Networks

Hands-On

  • Building a multi-layered perceptron for classification on SONAR dataset
5
Convolutional Neural Networks (CNN)

Learning Objectives:In this module, you’ll understand convolutional neural networks and its applications. You will learn the working of CNN, and create a CNN model to solve a problem.

 Topics:

  • Introduction to CNNs
  • CNNs Application
  • Architecture of a CNN
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing a CNN

Hands-On

Building a convolutional neural network for image classification. The model should predict the difference between 10 categories of images.


6
Recurrent Neural Networks (RNN)
7
Restricted Boltzmann Machine (RBM) and Autoencoders
8
Keras API

Learning Objectives:

In this module, you’ll understand how to use Keras API for implementing Neural Networks. The goal is to understand various functions and features that Keras provides to make the task of neural network implementation easy.

Topics:

  • Define Keras
  • How to compose Models in Keras
  • Sequential Composition
  • Functional Composition
  • Predefined Neural Network Layers
  • What is Batch Normalization
  • Saving and Loading a model with Keras
  • Customizing the Training Process
  • Using TensorBoard with Keras
  • Use-Case Implementation with Keras


Hands-On

  • Build a model using Keras to do sentiment analysis on twitter data reactions on GOP debate in Ohio


9
TFLearn API
10
In-Class Project

Learning Objectives:

In this module, you should learn how to approach and implement a project end to end. The instructor will share his industry experience and related insights that will help you kickstart your career in this domain. In addition, we will be having a QA and doubt clearing session for you.

Topics:

  • How to approach a project? 
  • Hands-On project implementation
  • What Industry expects?
  • Industry insights for the Machine Learning domain
  • QA and Doubt Clearing Session
According to payscale.com, the median salary for Deep Learning and TensorFlow Certified Engineer tops $120,000 per year.
Deep Learning is one of the most exciting and promising segments of Artificial Intelligence and machine learning technologies. The software industry now-a-days is moving towards machine intelligence. In fact, concepts within AI like Deep Learning with TensorFlow has become necessary in every sector generating lot of job opportunities worldwide.
This deep learning course with TensorFlow is all you need to master different deep learning algorithms and their implementation using TensorFlow, which is an open-source software library developed by Google building deep neural networks. By the end of this online instructor-led TensorFlow Training, you will be able to tackle real life industry grade projects based on deep learning and TensorFlow.
In order to master Deep Learning with Tensorflow you need following skills:
Understanding of Tensorflow concepts, its main functions, operations and the pipeline of execution
Building and training Deep Learning Models using TensorFlow
Understanding the working of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) and their applications
Proficiency in working with TFlearn, Autoencoders, Keras
Improving accuracy of deep learning models
Implementation of Restricted Boltz-mann Machine (RBM)
Performing Text Processing and Analysis
Deep learning is being applied on most of the AI related areas for better performance. Lots and lots companies are moving into Deep Learning to improve their model accuracy and therefore, making their product more efficient. There is an ample opportunity to apply Deep Learning & TensorFlow in the field of medicine, precision agriculture, etc.
The online Deep Learning with TensorFlow Certification course can be attended from anywhere as per your ease. The major key takeaways of an online TensorFlow Training over other offline trainings are: Latest Course Curriculum as per current industry standards and demands Live & Interactive Session: The class will be taken by an industry expert in an interactive fashion where you can clarify all your doubts in the class itself. Industry Grade Projects and Case Studies: In order to strengthen your subject knowledge, you will be provided with various industry grades projects and case studies. Lifetime Access & 24x7 support: You will be awarded with lifetime access to all of the the course content as well as class recordings which you can go through again anytime later. Besides this, we have our 24x7 support ninjas ready to clarify any of your doubts or help you out once you get stuck anywhere.
Deep Learning with TensorFlow Certification Training by Certs Learning has been carefully designed in such a way that both beginners and experts can go through it without facing any difficulties. The instructor will be available for you throughout the training period to ensure that you are able grasp all the concepts perfectly. Besides this, the 24x7 support ninjas are available to help you with all your issues and doubts.
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Lectures: 10