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Deep Learning With TensorFlow

  • Course level: Beginner

Description

Deep Learning With TensorFlow. “What is Deep Learning” video will help you to understand the relationship between Deep Learning, Machine Learning, and Artificial Intelligence and how Deep Learning came into the picture.

This Deep Learning With TensorFlow tutorial will be discussing Artificial Intelligence, Machine Learning, and its limitations, how Deep Learning overcame Machine Learning limitations, and different real-life applications of Deep Learning.

Why Learn Deep Learning With TensorFlow?

TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer, and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world.

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What Will I Learn?

  • 1.Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline.
  • 2.throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.
  • 3. What Is Artificial Intelligence?
  • 4. Learn What Is Machine Learning?
  • 5. Limitations Of Machine Learning
  • 6. Deep Learning To The Rescue
  • 7. Learn What Is Deep Learning?
  • 8. Deep Learning Applications

Topics for this course

36 Lessons

Deep Learning With TensorFlow Videos

What is Deep Learning00:00:00
Deep Learning Tutorial00:00:00
TensorFlow Tutorial00:00:00
Introduction To TensorFlow00:00:00
Introduction to Deep Learning00:00:00
Deep Learning With Python00:00:00
Artificial Intelligence00:00:00
What Is Artificial Intelligence?00:00:00
Neural Network Tutorial00:00:00
Artificial Neural Network Tutorial00:00:00
Recurrent Neural Networks (RNN)00:00:00
Convolutional Neural Network (CNN)00:00:00
Restricted Boltzmann Machine00:00:00
AI vs Machine Learning vs Deep Learning00:00:00
Top 8 Deep Learning Frameworks00:00:00
What Are Autoencoders?00:00:00
Autoencoders Tutorial00:00:00
TensorFlow TFLearn Tutorial00:00:00
What is a Neural Network00:00:00
PyTorch Python Tutorial00:00:00
Keras Tutorial For Beginners00:00:00
Keras Tutorial TensorFlow00:00:00
Deep Learning Using TensorFlow00:00:00
Machine Learning In Python00:00:00
TensorFlow Object Detection00:00:00
Backpropagation And Gradient Descent Tutorial00:00:00
Classifying Hand Written Digits Using TensorFlow00:00:00
Creating Chatbots Using TensorFlow00:00:00
TensorFlow Explained00:00:00
OpenAI 5 Explained00:00:00
Keras vs Tensorflow vs PyTorch00:00:00
TensorBoard Tutorial00:00:00
Deep Learning Interview Questions and Answers00:00:00
TensorFlow Installation00:00:00
Top Deep Learning Projects00:00:00
What Are GANs?00:00:00
65 £

Enrolment validity: Lifetime

Requirements

  • The following professionals can go for this course:
  • 1. Developers aspiring to be a 'Data Scientist'
  • 2. Analytics Managers who are leading a team of analysts
  • 3. Business Analysts who want to understand Deep Learning (ML) Techniques
  • 4. Information Architects who want to gain expertise in Predictive Analytics
  • 5. Professionals who want to captivate and analyze Big Data
  • 6. Analysts wanting to understand Data Science methodologies
  • However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.