Internet of Things

 1. Arduino board can withstand a maximum voltage of _________ - 20v

2. Photo diode is a/an ____________ electronic component.- Passive

3. ____________ is a standardized method to establish communication between interconnected devices. - Protocol

4. Implementing Edge/Fog computing helps to reduce network bandwidth- True

5.____________ is a suite of applications used to prepare and present data in a meaningful way - IoT Platform

6. The unique identifier of an IoT device helps - 

7. MQTT is an open OASIS and ISO standard lightweight, publish-subscribe network protocol that transports messages between devices

8.Raspberry Pi is a low-cost general-purpose computer.- True

9. Arduino Uno is pre-programmed with - boot loader

10. IoT infrastructure should support - anytime anywhere

11. Which of the following is a/are characteristic(s) of an IoT application? - Connectable and Scalable

12. WAN is not an IoT protocols 

13. Edge computing helps to reduce the latency time of processing information - TRUE

14. Arduino board can read sensor values through the analog I/O pins. - TRUE

15. Arduino is a microcontroller.  - False

16. The following are IoT platforms, except _________ Zoho Connect

17. 'Denial of Service' is a attack using interconnected PC or devices. - TRUE

18. Edge computing is - Processing the data near the device

19. ___________ is a specialized web transfer protocol for use with constrained nodes and networks in IoT. - CoAP

20. Identify the non-IoT device from the given options.- Microsoft Surface Laptop

21. Internet of Things is a system of interconnected computing devices. - True

22. Sensors and Actuators are also known as ___________ - Transducers

Deep Learning

1.       What is the method to overcome the Decay of Information through time in RNN known as?

·          Gating

2.       The measure of Difference between two probability distributions is know as  

·         KL Divergence

3.       Recurrent Network can input Sequence of Data Points and Produce a Sequence of Output

·         True

4.       Prediction Accuracy of a Neural Network depends on _______________ and ______________

·          Weight & Bias

5.       Process of improving the accuracy of a Neural Network is called –

·         Training

6.       The rate at which cost changes with respect to weight or bias is called __________________

·         Gradient

7.       A _______________ matches or surpasses the output of an individual neuron to a visual stimuli. –

·         Convolution

8.       Autoencoders cannot be used for Dimensionality Reduction.

·         FALSE

9.       Data Collected from Survey results is an example of _ -

·         Structured Data

10.   Recurrent Networks work best for Speech Recognition. –

·         True

11.   How do RNTS interpret words?

·          Vector representation

12.   De-noising and Contractive are examples of

·         Autoencoders

13.   Gradient at a given layer is the product of all gradients at the previous layers.

·         True

14.   A Deep Belief Network is a stack of Restricted Boltzmann Machines.

·         True

15.   What are the two layers of a Restricted Boltzmann Machine called ?

·         Visible and Hidden

16.   All the Visible Layers in a Restricted Boltzmann Machine are connected to each other.

·         False

17.   Name the component of a Neural Network where the true value of the input is not observed.

·         Hidden Layer

18.   What is the difference between the actual output and generated output known as?

·         Cost

19.   In a Neural Network, all the edges and nodes have the same Weight and Bias values.

·         False

20.   What does LSTM stand for?

·         Long Short Term memory

21.   RELU stands for _______________

·         Rectified Linear Unit

22.   A Shallow Neural Network has only one hidden layer between Input and Output layers.

·         True

23.   Restricted Boltzmann Machine expect the data to be labeled for Training.

·         False

24.   Support Vector Machines, Naive Bayes and Logistic Regression are used for solving _______________________ problems.

·         Classification

25.   _____________ is a recommended Model for Pattern Recognition in Unlabeled Data.

·         Autoencoders

26.   Recurrent Neural Networks are best suited for Text Processing.

·         True