edureka!
( Tensorflow Training – https://www.edureka.co/ai-deep-learning-with-tensorflow )
This Edureka “What is Deep Learning” video (Blog: https://goo.gl/4zxMfU) will help you to understand about the relationship between Deep Learning, Machine Learning and Artificial Intelligence and how Deep Learning came into the picture. This tutorial will be discussing about Artificial Intelligence, Machine Learning and its limitations, how Deep Learning overcame Machine Learning limitations and different real-life applications of Deep Learning.
Below are the topics covered in this tutorial:
1. What Is Artificial Intelligence?
2. What Is Machine Learning?
3. Limitations Of Machine Learning
4. Deep Learning To The Rescue
5. What Is Deep Learning?
6. Deep Learning Applications
Subscribe to our channel to get video updates. Hit the subscribe button above.
Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
– – – – – – – – – – – – – –
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!
– – – – – – – – – – – – – –
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.
– – – – – – – – – – – – – –
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.
– – – – – – – – – – – – – –
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.
Please write back to us at sales@edureka.co or call us at +91 88808 62004 for more information.
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Source
very nice video
waiting for other videos … awesome video … great explanation
Awesome work guys, keep up the good work….
Awesomely put crisp and to the point session. Thank you for sharing. Keep up the effort.
Awesome.Is there any PPT/PDF slides available?
Thanks Sir. You are simply awesome 🙂
can u please give more tutorial on deep learning
Nice introductory session for the beginners to learn about deep learning. Pretty sorted on point things said in the video. Its a great help. Thanks
Edureka is the best place to learn new technologies! Love it. Amazing efforts by all instructors to help learners. Awesome channel!
Great tutorial !!! Just have one question now a days lot of things coming in Ml and deep learning, so I am now confused from where to start ? I am thinking to start tensorflow and gain deep knowledge in it ? Is it the right choice ?
Wow awesome video.It's much useful & interesting…Hatsoff to you guys
There is very high pollution in Delhi. Can ANN or Deep learning solve the problem?
Thanks For giving me Link for the Playlist
i am having confusion in which course should i select for my intern topics are 1)Human Computer Interaction using Deep Learning.2)Digital system design. Internet-of-Things (IoT) based system. 3D modeling of buildings. Mobile and Web App development.3)Machine learning and Data Analytics in Software Engineering or Web Services.
this is awesome
Excellent session
Is it Possible to train Deep Learning Models on Gt840M?
hi,I before watching Edureka Deep learning video i don't have knowledge about deep learning but after watching i clearly understand(perfectly ) about deep learning .i really thanks for video making team.
Thanks for sharing these interesting materials. Could it be possible to
allow me (and others) to contribute to translations? Because in my
country (and others) people are not necessarily good enough in English
to understand. It would be very helpful and the world would become
better.
In the machine learning example of flowers how can the machine develop a relation between sepal length, width , etc without us mentioning it.
Nice Explanation and Thanks Edureka
Machines Do Get Tired
This is the first time I've understood what deep learning is.
waooooo
I have one question??? Sir What is the actual meaning of Weight ? U have specified weight in the example of deep learning..
sir can you explainmath behind
the face recognition
Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka AI & Deep Learning Course curriculum, Visit our Website: http://bit.ly/2r6pJuI
Videos are excellent!!
Woh.
Its fantastic.