Deep Learning Interview Questions And Answers | AI & Deep Learning Interview Questions | Intellipaat

Intellipaat

🔥Intellipaat AI Deep Learning course: https://intellipaat.com/artificial-intelligence-masters-training-course/
In this deep learning interview questions and answers you will learn the latest and top questions asked by companies for deep learning interview. This deep learning interview questions & answers video covers all kinds of questions starting from basic to advanced questions so that you can get benefited.
#DeepLearningInterviewQuestionsAndAnswers #AIandDeepLearningInterviewQuestions #DeepLearningInterviewQuestions #DeepLearningInterview #DeepLearning #MachineLearning #AIInterviewQuestions

📌 Do subscribe to Intellipaat channel & get regular updates on videos: http://bit.ly/Intellipaat

🔗 Watch AI video tutorials here: http://bit.ly/2F1Bhqt

📕 Read complete AI tutorial here: https://intellipaat.com/blog/tutorial/artificial-intelligence-tutorial/

📝Following questions are covered in this deep learning video:
00:00 – Deep Learning Interview Questions And Answers
00:59 – What is the Difference between Machine Learning and Deep Learning?
02:16 – What is Perceptron?
03:26 – How is Deep Learning better than Machine Learning?
04:29 – What are some of the most used applications of Deep Learning?
05:27 – What is the meaning of Over fitting?
06:47 – What are Activation functions?
08:00 – Why is Fourier transform used in Deep Learning?
08:55 – What are the steps involved in training a perceptron in Deep learning?
09:47 – What is the use of the loss function?
10:30 – What are some of the Deep Learning Frameworks or tools that you have used?
11:49 – What is the use of the swish function?
12:38 – What are auto encoders?
13:41 – What are the steps to be followed to use the gradient descent algorithm?
14:57 – Differentiate between a single layer perceptron and a multi-layer perceptron
16:00 – What is data normalization in Deep Learning?
16:54 – What is forward propagation?
17:44 – What is back propagation?
18:40 – What are Hyper parameters in Deep Learning?
19:19 – How can hyper parameters be trained in neural networks?
21:38 – What is the meaning of dropout in Deep Learning?
22:42 – What are Tensors?
23:44 – What is the meaning of model capacity in Deep Learning?
24:33 – What is Boltzmann Machine?
25:25 – What are some of the advantages of using TensorFlow?
26:27 – What is the computational graph in Deep Learning?
27:40 – What is a CNN?
28:25 – What are the various layers present in a CNN?
30:19 – What is an RNN in Deep Learning?
31:15 – What is a Vanishing gradient when using RNNs?
32:11 – What is exploding gradient descent in Deep Learning?
33:10 – What is the use of LSTM?
34:04 – Where are autoencoders used?
35:05 – What are the types of auto encoders?
35:35 – What is a restricted Boltzmann Machine?
36:30 – What are some of the limitations of Deep Learning?
38:04 – What are the variants of gradient descent?
39:33 – Why is mini-batch gradient descent so popular?
40:35 – What are deep autoencoders?
41:47 – Why is the leaky ReLu function used in Deep Learning?
42:35 – What are some of the examples if the supervised learning algorithms in Deep Learning?
43:25 – What are some of the examples of unsupervised learning algorithms in Deep Learning?
43:56 – Can we initialize the weights of a network to start from zero?
45:00 – What is the meaning of valid padding and same padding in CNN?
46:16 – What are some of the applications of transfer learning in Deep Learning?
47:25 – How is the transformer architecture better than RNNs in Deep Learning?
48:41 – What are the steps involved in the working of an LSTM network?
50:07 – What are the elements in TensorFlow that are programmable?
50:43 – What is the meaning of bagging and boosting in Deep Learning?
51:52 – What are generative adversarial networks (GANs)?
53:00 – Have you earned any sort of Certification to improve your learning and implementation process?
—————————-
Intellipaat Edge
1. 24*7 Life time Access & Support
2. Flexible Class Schedule
3. Job Assistance
4. Mentors with +14 yrs
5. Industry Oriented Course ware
6. Life time free Course Upgrade
——————————
Why should you opt for an Artificial Intelligence career?

If you want to fast-track your career then you should strongly consider Artificial Intelligence. The reason for this is that it is one of the fastest growing technology. There is a huge demand for professionals in Artificial Intelligence. The salaries for A.I. Professionals is fantastic.There is a huge growth opportunity in this domain as well.
——————————

For more Information:
Please write us to sales@intellipaat.com, or call us at: +91- 7847955955, US : 1-800-216-8930(Toll Free)

Website: https://intellipaat.com/artificial-intelligence-masters-training-course/

Facebook: https://www.facebook.com/intellipaatonline

LinkedIn: https://www.linkedin.com/company/intellipaat-software-solutions

Twitter: https://twitter.com/Intellipaat

Source