Deep Learning Interview Questions And Answers | AI & Deep Learning Interview Questions | 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 [email protected], 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