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For Batch - 2017 to 2021 & 2018 to 2022
Note: Only one course has to be opted from course-4 & course-5.
For Batch - 2019 to 2023
Note: Only one course has to be opted from course-2 & course-3.
For Batch - 2020 to 2024 & 2021 to 2023
Note: Only one course has to be opted from course-2 & course-3.
https://www.predictiveanalyticsworld.com/book/pdf/Predictive_Analytics_by_Eric_Siegel_Excerpts.pdf
6.1 Fundamentals of Video Processing: Digital Video Acquisition, Principles of Color Video,
Video Camera, Video Display, Analog Vs Digital Video: Progressive Vs Interlaced scans, Signal, Bandwidth Characterization of a Digital Video Signal.
Practice:
6.2 Fourier Analysis of Digital Video Signals: Spatial and Temporal resolution, Fourier Analysis of Digital Video Signals, Spatial-Temporal Sampling: Temporal Frequency Response and Flicker Perception. Spatial Frequency Response, Spatiotemporal Frequency Response, Smooth Pursuit Eye Movement
Practice:
6.3 Digital Video Formats: Significance of Video Formatting, Data rate and bandwidth trade-off, File Formats: MP4, MOV, WMV, AVCHD, FLV, AVI, WebM, MKV
Digital Video Compression Standards: Digital Video Compression Metrics, Digital Video Storage Precisions, Significance of Video compression, Video Compression Codec’s: Motion JPEG, JPEG 2000, H.264/MPEG-4 AVC, VP8, HEVC, H.265 High Efficiency Video Codec.
Practice:
6.4 Digital Video Editing Basics: Video Editing Types- Online, Offline, Linear, Non-linear, Assemble, Insert, Rough-cut, Video Shot Transition Effects: Cut, Fade, Wipe, Dissolve, B-roll, Video Shot Boundary Detection Methods: pixel differences, statistical differences, histogram comparisons, edge differences and motion vectors. Video Shot Detection Performance Metrics: ROC Curves, Recall, Precision, F-Measure
Practice:
Project List
TEXT BOOK:
REFERENCE BOOK:
8.1 Defining IoT Analytics and Challenges
IoT
Benefits of Deploying IoT
End to End IoT architecture
IoT challenges
8.2 IoT Protocols
8.2.1 Wireless Protocol
Connectivity Protocols (when Power is Limited)
Bluetooth Low Energy (BLE)
Zigbee
LoRaWAN
NFC
8.2.2 Connectivity Protocols (when Power is Not a problem)
Wifi
8.2.3 Data Communication Protocol
MQTT
Web-Socket
HTTP
8.2 Sensors
Types of Sensors based on communication-I2C, SPI
Types of Sensors based on Application
8.3 Overview of 32 -bit Controller
ESP8266
ESP32
Raspberry Pi
8.4 AWS IoT for Cloud
AWS IoT Core services
AWS IoT Analytics services
AWS DynamoDB Services
8.5 Thingspeak for IoT
Getting and posting Data to IoT Cloud using ESP devices
Posting Data to IoT Cloud using Raspberry Pi
8.6 ThingWorx for Industrial IoT
Building Dashboard on Thingworx platform
Binding the senor value to the dashboard
Text Book:
Reference Books:
2. Geng, Hwaiyu, ed. Internet of things and data analytics handbook. John Wiley & Sons, 2017.
11.1 When Models Meet Data:-
11.2 Linear Regression:-
11.3 Dimensionality Reduction with Principal Component Analysis:-
11.4 Density Estimation with Gaussian Mixture Models:-
11.5 Classification with Support Vector Machines:-
Practice:
References:
1. Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, Cheng
Soon Ong.
2. https://youtube.com/playlist?list=PLLy_2iUCG87D1CXFxE-SxCFZUiJzQ3IvE
Course objective, outcome, methodology and assessment.
Why data visualisation
Story telling using Visuals & Infographics
https://venngage.com/blog/9-types-of-infographic-template/#1
https://www.edugrad.com/tutorials/learn-data-visualization-using-python/15
Tips on good visuals
https://statedashboard.odisha.gov.in/
https://www.youtube.com/watch?v=4pymfPHQ6SA
Project Groups:
Students will be divided into groups and assigned projects. Each group will do two projects.
Practice
Environmental setup - Anaconad and Jupyter notebook, Anaconda Navigator and Libraries Installation
Practice
Python Fundamentals, Use Case - Data Analysis, Exploring and learning assignments on Jupyter Notebook
https://towardsdatascience.com/data-visualization-say-it-with-charts-in-python-138c77973a56
https://towardsdatascience.com/plotting-with-python-c2561b8c0f1f
https://towardsdatascience.com/introduction-to-data-visualization-in-python-89a54c97fbed
Project - 1
For Project -1, the student group has to define the objective/s of the study, identify the data that will be needed and the source of such data
Make Presentations groupwise
Practice
Data collection/importing and reading using Python function of different types of files, i.e. CSV, HTML, Excel - Get CSV data files from source and read them, get HTML file and read, Get Excel sheet and read
https://perso.telecom-paristech.fr/eagan/class/igr204/datasets
https://www.youtube.com/watch?v=eWFwe41LyWk
https://towardsdatascience.com/wrangling-data-with-pandas-27ef828aff01
https://www.youtube.com/watch?v=ndwuUzgAiPY
https://www.youtube.com/watch?v=Ycq3sDg6ji0
Sorting data, Missing values & Munging data
https://www.youtube.com/watch?v=-dwjEfv2R50
https://www.youtube.com/watch?v=EaGbS7eWSs0
Project - 1
Data collection and sorting for the assigned project
Pandas Tutorial 1. What is Pandas python? Introduction and Installation- https://www.youtube.com/watch?v=CmorAWRsCAw
Pandas Tutorial2. Dataframe and Series Basics- Selecting row and column- https://www.youtube.com/watch?v=zmdjNSmRXF4
Pandas Tutorial 3: Different Ways Of Creating DataFrame - https://www.youtube.com/watch?v=3k0HbcUGErE
Python Pandas Tutorial 4: Read Write Excel CSV File- https://www.youtube.com/watch?v=-0NwrcZOKhQ
Importing data in python - Read excel file - https://www.youtube.com/watch?v=lco-r5CgvhY
Pandas Tutorial 8 | How to import HTML data in Python | Importing HTML data in Python - https://www.youtube.com/watch?v=ndwuUzgAiPY
Pandas Tutorial 13, Crosstabs - https://www.youtube.com/watch?v=I_kUj-MfYys
Practice
Basics of Numpy
https://www.youtube.com/watch?v=xECXZ3tyONo
Complete Python NumPy Tutorial (Creating Arrays, Indexing, Math, Statistics, Reshaping) - https://www.youtube.com/watch?v=GB9ByFAIAH4
Practice
Basic of Matplotlib
https://www.youtube.com/watch?v=MbKrSmoMads&pbjreload=10
Matplotlib Tutorial 1 - Introduction and Installation- https://www.youtube.com/watch?v=qqwf4Vuj8oM
Matplotlib Tutorial 2 - format strings in plot function - https://www.youtube.com/watch?v=zl5qPnqps8M
Matplotlib Tutorial 3 - Axes labels, Legend, Grid- https://www.youtube.com/watch?v=oETDriX9n1w
Matplotlib Tutorial 4 - Bar Chart - https://www.youtube.com/watch?v=iedmZlFxjfA
Matplotlib Tutorial 5 - Histograms - https://www.youtube.com/watch?v=r75BPh1uk38
Matplotlib Tutorial 6 - Pie Chart - https://www.youtube.com/watch?v=GOuUGWGUT14
Matplotlib Tutorial 7 - Save Chart To a File Using savefig - https://www.youtube.com/watch?v=XLJHkCn48lM
Plotting real-time data using Python - https://www.youtube.com/watch?v=GIywmJbGH-8
Project (work on Project -1)
Work on the projects assigned using Python Libraries
Pandas Tutorial 1. What is Pandas python? Introduction and Installation- https://www.youtube.com/watch?v=CmorAWRsCAw
Pandas Tutorial 3: Different Ways Of Creating DataFrame - https://www.youtube.com/watch?v=3k0HbcUGErE
Python Pandas Tutorial 4: Read Write Excel CSV File
https://www.youtube.com/watch?v=-0NwrcZOKhQ
Importing data in python - Read excel file - https://www.youtube.com/watch?v=lco-r5CgvhY
Pandas Tutorial 8 | How to import HTML data in Python | Importing HTML data in Python - https://www.youtube.com/watch?v=ndwuUzgAiPY
Pandas Tutorial 13, Crosstabs - https://www.youtube.com/watch?v=I_kUj-MfYys
Practice
Plotly
https://plotly.com/python/basic-charts/
Graphing Library - https://plotly.com/python/
Plotly Python - Plotly multi line chart| Plotly Python data visualization- https://www.youtube.com/watch?v=pfhBbJ2MnMI
Plotly Data Visualization in Python | Part 13 | how to create bar and line combo chart - https://www.youtube.com/watch?v=AQG4RQolUC8
Plotly Web based visualisation - https://www.youtube.com/watch?v=B911tZFuaOM
Project (Project-1)
Work on Project
Interim Presentation
Practice
Seaborn - Scatter Chart, Bubble Chart, Gapminder
https://www.youtube.com/watch?v=MGOcVAOuXxo
https://www.tutorialspoint.com/seaborn/seaborn_tutorial.pdf
Interactive Data Visualization - https://www.youtube.com/watch?v=VdWfB30QTYI
Practice
Web Scrapping
https://www.youtube.com/watch?v=mKxFfjNyj3c
Web scraping in Python (Part 4)_ Exporting a CSV with pandas - https://www.youtube.com/watch?v=Zh2fkZ-uzBU
Web scraping in Python (Part 2)_ Parsing HTML with Beautiful Soup - https://www.youtube.com/watch?v=zXif_9RVadI
Webscraping - Mode, Median, Mean, Range, and Standard Deviation- https://www.youtube.com/watch?v=mk8tOD0t8M0
Web Scraping Dynamic Graphs to CSV Files using Python - https://www.youtube.com/watch?v=NYK_1bVoBfU
Practice
Solve the 10 problem (started from session 7)
-students will submit the assignment (in groups)
(upload the assignment ...done by Prof. Ramana)
Practice
Dashboard Basics
https://www.youtube.com/watch?v=e4ti2fCpXMI
Create Presentation Slides from Jupyter - https://www.youtube.com/watch?v=utNl9f3gqYQ
Dash and Python 1_ Setup -https://www.youtube.com/watch?v=Ldp3RmUxtOQ
Dash and Python 2_ Dash Core Components - https://www.youtube.com/watch?v=NM8Ue4znLP8
Dash and Python 3_ Using CSS - https://www.youtube.com/watch?v=x9mUZZ19dl0
Practice
Dash (plotly) and Python
https://www.youtube.com/watch?v=Ldp3RmUxtOQ
Dash in 5 Minutes - https://www.youtube.com/watch?v=e4ti2fCpXMI
How to Create a Slideshow using Jupyter+Markdown+Reveal.js- https://www.youtube.com/watch?v=EOpcxy0RA1A
ipython dashboard - https://www.youtube.com/watch?v=LOWBEYDkn90
Plotting real-time data using Python - https://www.youtube.com/watch?v=GIywmJbGH-8
Practice
Interactive charts/Maps using Bokeh,
Dash board using Dash
https://www.youtube.com/watch?v=o4TB6LTPDaY
Practice
IPython-Dashboard
Live graphs
https://pypi.org/project/IPython-Dashboard/
https://pythonprogramming.net/live-graphs-data-visualization-application-dash-python-tutorial/
Project
Work on Project - 1 to make dash boards
Project
Final presentation of Project -1
Project -2
Start Project - 2 (ERP Dash Board)
Define the objective and prepare the flow chart
Project
Make presentations on the objective and flow chart of Project-2
Project
Work on Project - 2
Project
Make interim presentation on Project - 2
Project
Work on Project - 2
Project
Final Presentation on Project -2
Project
Make final changes on Project -1 & Project -2 to make it ready for External Evaluation
https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html
https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html
Principal component analysis (PCA) sessions 11,12
Linear discriminant analysis (LDA)-sessions 13,14
Logistic Regression (Multiclass Classification)-sessions 24,25,26
Root Mean Square Error (RMSE)-sessions 42,43
Mean Average Percentage Error (MAPE)-session-44,45
Mean Average Percentage Error (MAPE) - sessions 44,45
Confusion Matrix (TN, TP, FP, FN) -sessions 46,47
Sensitivity, Specificity, Overall Accuracy-session-48,49
Receiver Operating Characteristic ROC Curve -sessions 50,51,52
Receiver Operating Characteristic ROC Curve-session-50,51,52
Dimensionality-reduction-and-classification-on-Hyperspectral-Images-Using-Python
Dimensionality-reduction-and-classification-on-Hyperspectral-Images-Using-Python
Practice 1:
Creating Things, Certificates, Policies in AWS IoT core Services
Practice 2:
Connect NodeMCU with AWS IoT Core Services
Practice 3:
Connect ESP32 with AWS IoT Core Services
Practice 4:
Connect Raspberry Pi with AWS IoT Core Services
Practice 5:
Posting Sensor Data to AWS IoT Core Services
Practice 6:
Controlling Devices from AWS IoT Core Services
Practice 7:
Storing Sensor Data into DynamoDB using AWS IoT core
Practice 8:
Get Raspberry Pi to interact with Amazon Web Services & push data into the DynamoDB
Practice 9:
Posting Sensor Data to the Thingspeak to aggregate, visualize and analyze live data streams in the cloud
Practice 10:
Portable IoT Based Fingerprint Biometric Attendance System
Practice 11:
IoT-based Covid Patient Blood Oxygen monitor & calling an ambulance on critical blood oxygen levels
Session -1, 2
Digital Video Acquisition, Principles of Color Video
https://www.slideshare.net/MazinAlwaaly/multimedia-color-in-image-and-video
http://what-when-how.com/introduction-to-video-and-image-processing/image-acquisition-introduction-to-video-and-image-processing-part-1/
Session -3, 4
Video Camera, Video Display,
https://www.youtube.com/watch?v=Gnl1vuwjHto
Session -5
Analog Vs Digital Video
Session -6,7
Progressive Vs Interlaced scans
https://www.youtube.com/watch?v=ZJXczn_jPLQ
Session - 8,9
Signal, Bandwidth Characterization of a Digital Video Signal.
https://www.youtube.com/watch?v=xAc4TSp87IY
https://nptel.ac.in/content/storage2/courses/117104020/Lecture/Lec3.pdf
Session - 10,11
Spatial and Temporal resolution.
Spatial and Temporal resolution
https://www.youtube.com/watch?v=ePp2es3nvDA
https://www.youtube.com/watch?v=zY-Eej5d_lo
Session -12
Fourier Analysis of Digital Video Signals
https://eeweb.engineering.nyu.edu/~yao/EL6123old/FT.pdf
Session -13, 14
Temporal Frequency Response and Flicker Perception
https://www.youtube.com/watch?v=E-5p26RfkMo
https://eeweb.engineering.nyu.edu/~yao/EL6123old/FT.pdf
Session -15, 16
Spatial Frequency Response, Spatiotemporal Frequency Response
https://eeweb.engineering.nyu.edu/~yao/EL6123old/FT.pdf
https://www.youtube.com/watch?v=a-rHXtGLyI0
Session -17
Smooth Pursuit Eye Movement
https://www.slideshare.net/AdeWijaya5/smooth-pursuit-eye-movement
Session -18
Significance of Video Formatting
https://www.rev.com/blog/resources/benefits-of-different-video-formats
Session -19,20
Data rate and bandwidth trade-off
Session -21
File Formats: MP4, MOV, WMV, AVCHD, FLV, AVI, WebM, MKV
https://www.rev.com/blog/resources/benefits-of-different-video-formats
https://www.youtube.com/watch?v=x6sSfIG8o3U&t=68s
Session -22
Digital Video Compression Standards
https://www.mistralsolutions.com/articles/video-compression-standards-pros-cons/
Session -23
Digital Video Compression Metrics
https://link.springer.com/chapter/10.1007/978-1-4302-6713-3_4
Session -24,25
Digital Video Storage Precisions
https://www.youtube.com/watch?v=SPvdHvxF--Q
Session -26,27
Significance of Video compression,
https://www.slideshare.net/Shreyash03/video-compression-74491649
Video Compression Codec’s: Motion JPEG, JPEG 2000, H.264/MPEG-4 AVC, VP8, HEVC, H.265 High Efficiency Video Codec.
https://www.youtube.com/watch?v=-4NXxY4maYc&t=358s
Session - 28,29
Video Editing Basics
https://www.slideshare.net/TANZICT/video-editing-16421406
Session -30,31
Video Editing Types- Online, Offline, Linear, Non-linear
https://filmdaft.com/video-editing-101-the-different-types-of-video-editing/
https://www.youtube.com/watch?v=YEFu0zRiVD4
https://www.youtube.com/watch?v=PH5I8Y7RXi8
Session -32,33
Assemble, Insert, Rough-cut
https://www.youtube.com/watch?v=4TQugiLxneY
https://www.youtube.com/watch?v=l1C34QmGuIA
Session -34, 35
Video Shot Transition Effects: Cut, Fade, Wipe, Dissolve, B-roll
https://www.youtube.com/watch?v=sgYX1c8rczk
https://www.masterclass.com/articles/what-is-b-roll-footage-and-how-can-you-use-it#what-is-broll
Session -36, 37
Video Shot Boundary Detection Methods: pixel differences
https://www.youtube.com/watch?v=7AlwDYmjrcs&list=PL2zRqk16wsdqXEMpHrc4Qnb5rA1Cylrhx
http://ceur-ws.org/Vol-2589/Paper6.pdf
Session -38,39
Video Shot Boundary Detection Methods: statistical differences, histogram comparisons
https://www.youtube.com/watch?v=mlacCuKnedM
http://ceur-ws.org/Vol-2589/Paper6.pdf
http://www.tjprc.org/publishpapers/tjprcfile172.pdf
Session -40, 41
Video Shot Boundary Detection Methods: edge differences and motion vectors
http://www.tjprc.org/publishpapers/tjprcfile172.pdf
Session -42, 43
Video Shot Detection Performance Metrics: ROC Curves, Recall, Precision, F-Measure
https://medium.com/swlh/recall-precision-f1-roc-auc-and-everything-542aedf322b9
https://www.youtube.com/watch?v=8d3JbbSj-I8
https://www.youtube.com/watch?v=MUCo7NvB9SI
Session -1
Data, Models, and Learning
session-2
Empirical Risk Minimization
session-3
Parameter Estimation
session-4
Probabilistic Modelling and Inference
session-5
Directed Graphical Models
session-6
Model Selection
session-7
Problem Formulation
session-8
Parameter Estimation
session-9
Bayesian Linear Regression
session-10
Maximum Likelihood as Orthogonal Projection
session-11
Problem Setting
session-12
Maximum Variance Perspective
session-13
Projection Perspective
session-14
Eigenvector Computation and Low-Rank Approximations
session-15
PCA in High Dimensions
session-16
Key Steps of PCA in Practice
session-17
Latent Variable Perspective
session-18
Gaussian Mixture Model
session-19
Parameter Learning via Maximum Likelihood
session-20
EM Algorithm
session-21
Latent-Variable Perspective
session-22
Separating Hyperplanes
session-23
Primal Support Vector Machine
session-24
Dual Support Vector Machine
session-25
Kernels
session-26
Numerical Solution
Dr. Sujata Chakravarty is a Senior Member of IEEE. Her research area includes multidisciplinary fields like Application of Computational Intelligence and Evolutionary Computing Techniques in the field of Financial Engineering, Bio-medical data classification, Smart Agriculture, Intrusion Detection System in Computer-Network, Analysis and prediction of different financial time series data. She is a reviewer of many […]
Manoj Kumar Behera, M. tech. in Computer Science, NIT Rourkela, Qualified GATE in 2008. His research area includes application of machine learning and image processing in the fields of smart agriculture and Bio-medical applications. He has published about 20 articles in many international journals and conferences.