PyTorch Python Tutorial | Deep Learning Using PyTorch | Image Classifier Using PyTorch | Edureka

///PyTorch Python Tutorial | Deep Learning Using PyTorch | Image Classifier Using PyTorch | Edureka

PyTorch Python Tutorial | Deep Learning Using PyTorch | Image Classifier Using PyTorch | Edureka

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( ** Deep Learning Training: ** )
This Edureka PyTorch Tutorial video (Blog: will help you in understanding various important basics of PyTorch. It also includes a use-case in which we will create an image classifier that will predict the accuracy of an image data-set using PyTorch.

Below are the topics covered in this tutorial:

1. What is Deep Learning?
2. What are Neural Networks?
3. Libraries available in Python
4. What is PyTorch?
5. Use-Case of PyTorch
6. Summary

Check our complete Deep Learning playlist:

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How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course
Edureka’s Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.

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Who should go for this course?

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.

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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 over 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.

For more information, please write back to us at or call us at IND: 9606058406 / US: 18338555775 (toll-free).


By |2021-02-16T12:29:40+00:00February 16th, 2021|Python Video Tutorials|10 Comments


  1. edureka! February 16, 2021 at 12:29 pm - Reply

    Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.
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  2. Pandian Ambairam February 16, 2021 at 12:29 pm - Reply

    very nice explanation.

  3. The Black Knight February 16, 2021 at 12:29 pm - Reply

    One of the best channel for Working professionals, because we can not go 30 videos to learn a technology due to time-constrained and edureka gives us basic level understanding in one video.

  4. Hisham Ragheb February 16, 2021 at 12:29 pm - Reply

    That was really interesting. Thanks

  5. Sai Nikhil Gona February 16, 2021 at 12:29 pm - Reply

    Nice one bro

  6. Diana Magzhanova February 16, 2021 at 12:29 pm - Reply

    what is tensors?

  7. Saikushal Mandala February 16, 2021 at 12:29 pm - Reply

    can i get the codes

  8. Michał Lis February 16, 2021 at 12:29 pm - Reply

    Thanks! Great video 🙂

  9. Jayanth G February 16, 2021 at 12:29 pm - Reply

    A very good start, it was very much informative….
    The introduction given to the new concepts were pretty much clear and easy to take in…
    Thank you 🙂

  10. Sandhya Iyer February 16, 2021 at 12:29 pm - Reply

    Damn nice! Good work!!

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