Simplilearn
This Deep Learning tutorial will help you in understanding what is Deep learning, why do we need Deep learning, applications of Deep Learning along with a detailed explanation on Neural Networks and how these Neural Networks work. Deep learning is inspired by the integral function of the human brain specific to artificial neural networks. These networks, which represent the decision-making process of the brain, use complex algorithms that process data in a non-linear way, learning in an unsupervised manner to make choices based on the input. This Deep Learning tutorial is ideal for professionals with beginners to intermediate levels of experience. Now, let us dive deep into this topic and understand what Deep learning actually is.
Below topics are explained in this Deep Learning Tutorial:
1. What is Deep Learning? ( 02:25 )
2. Why do we need Deep Learning? ( 03:42 )
3. Applications of Deep Learning ( 04:55 )
4. What is Neural Network? ( 11:32 )
5. Activation Functions ( 15:50 )
6. Working of Neural Network ( 26:14 )
Check Out Simplilearn Deep Learning Course here: https://www.simplilearn.com/deep-learning-course-with-tensorflow-training?utm_campaign=What-is-Deep-Learning-FbxTVRfQFuI&utm_medium=Tutorials&utm_source=youtube
To learn more about Deep Learning, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1
You can also go through the Slide here: https://goo.gl/EX98sh
Watch more videos on Deep Learning: https://www.youtube.com/playlist?list=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip
#DeepLearning #Datasciencecourse #DataScience #SimplilearnMachineLearning #DeepLearningCourse
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Simplilearn’s Deep Learning course will transform you into an expert in deep learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our deep learning course, you’ll master deep learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as deep learning scientist.
Why Deep Learning?
It is one of the most popular software platforms used for deep learning and contains powerful tools to help you build and implement artificial neural networks.
Advancements in deep learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in deep learning models, learn to operate TensorFlow to manage neural networks and interpret the results.
You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
4. Build deep learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial neural networks
6. Troubleshoot and improve deep learning models
We recommend this deep learning online course particularly for the following professionals:
1. Software engineers
2. Data scientists
3. Data analysts
4. Statisticians with an interest in deep learning
For more information about Simplilearn’s courses, visit:
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One of the best explanations !! Bravo …
I am in love with your videos. It cant be explained better. Kudos!
Based on experience, what is the highest success probability that can be achieved for a model? Is a 100% success probable?
I want to dawnload that presentation
Awesome video, thanks a lot buddy…..
This tutorial is very simple and gives a clear understanding of Deep Learning.Thank you for sharing this.
Thanks sir for explaining deep learning
😆
Very good introduction to ML and DL. A must read
Congratulations and post more such videos
Nice Video!
Could you please send the data and presentation slides on "yogeshbhilare.186@gmail.com"
very interesting and clear introduction . keept up !!!!! what about the next vedio
I was badly looking for such great online tutorials for Data Science and thanks team for such great videos of AI, ML, DL. I would definitely come back to you with my doubts if I get any. Thanks a lot again
Make video on machine learning and slowly speech some students don't understands easily
i was clueless for months and i finally understood what deep learning actually means within a day. Thank you sir!!
Awesome video , could you please tell me how cost function will be decided in the case of attack detection in cyber security. Like what will be the actual value?
I was badly looking for such awesome deep learning training thank you Simplilearn
Excellent Introduction about Deep Learning. Thanks a lot. Instructor is so patiently and gracefully taking the presentation..Wow!!
I have been wondering for ages what deep learning really is and how mathematics is relevant to deep learning but this video has by and large answered my questions! Thank you Simplilearn and I look forward to watching more of your videos!
Thank you very much. I'm preparing for an internship interview, this helped refresh my memory.
very nice explanation
thank u for providing slide
Great Tutorial !! Especially, repeating things and that too with such simplicity made everything really easy to understand. Thanks.
Thank you very much sir, it's really nice and very helpful for clear visualization. But i have a question . Can you help me please ?
When the cost function is convex then gradient descent method is best to minimize the cost function because convex function has global minimum and no local minimum , but for non-convex function which has suppose two local minimum how we can find out the global minimum ? what optimization technique can we use for non-convex cost function?
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One of the best explanations !! Bravo …
It is nice in a concise way,relation to higher degree is need of the hour.
I was badly looking for such awesome deep learning training thank you Simplilearn