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VLFM - Visionary Leaders for Manufacturing [ Home Page ]

PGPEX-VLFM Joint Post Graduation Program for Executives

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Artificial Intelligence and Machine Learning for Maufacturing Management

Table of Content
03 - Lecture Slides
1. Lecture Slides
  • Day01 - Introduction and Basics of Python-1 (Basics of Python, Syntax, Operators, Variable) | Click Here
  • Day02 - Basics of Python-2 (If-else, Loops, Functions, Math Library, Strings) | Click Here
  • Day03 - Advanced Python-1 (Data Structure in Python - List and Dictionary) | Click Here
  • Day04 - Advanced Python-2 (Data Structure in Python - Tuple and Sets) | Click Here
  • Day05 - Advanced Python-3 (Random Number-String, File Handling) | Click Here
  • Day06 - Introduction to Machine Learning | Click Here
- [DataSet] Sample Data Set - Click Here
- [Web Link] Teachable Machine Learning - Click Here
- [Video] Teachable Machine Learning - Click Here
  • Day07 - Correlation and Univariate/Multivariate Regression | Click Here
  • Day08 - Model Evaluation Parameters for Regression, Classification and Clustering) | Click Here
  • Day09 - PyCaret Automated Machine Learning Library for Regression | Click Here
  • Day10 - PyCaret Automated Machine Learning Library for Classification | Click Here
  • Day11 - PyCaret Automated Machine Learning Library for Clustering | Click Here
  • Day12 - Multi Decision Criteria using TOPSIS | Click Here
  • Day13 - Principal Component Analysis | Click Here
  • Day14 - Data Generation using Modelling and Simulation | Click Here
  • Day15 -
  • Day16 -
  • Day17 -
  • Day18 -
04 - Lab Experiments
2. Lab Experiments
  • Lab01 - Python Installation, Google Colab, Github, Google Dataset Search, Kaggle, Anaconda
    • [Explore Video 1] Learn How to use Google Colab | Link1   Link2   Link3  Link4  Link5
    • [Explore Video 2] Learn How to use Github | Link1    Link2  
    • [Explore Web 1] Explore Google Dataset Search | Click Here
    • [Explore Web 2] Explore Kaggle (Compete, Datasets, Notebooks, Jobs, more) | Click Here
    • Download & Install Anaconda for Python | Click Here to download
      Default Editor → Spyder  |  To start python idle → Open "Anaconda Prompt" and write "idle"
    • Practice: Lecture of Day02 | Click Here
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  • Lab02 - Basics of Python, Loops, Functions, String, Exception Handling
    • [Explore Video 1] How To Learn Data Science by Self Study and For Free | Click Here
    • [Explore Video 2 (imp)] How To Learn Data Science Smartly? | Click Here
    • [Explore Video 3] Role of Maths in Data Science | Click Here
    • [Explore Video 4] Step By Step Transition Towards Data Science | Click Here
    • [Explore Video 5] Complete Life Cycle of a Data Science Project | Click Here
    • [Explore Video 6] Step By Step Action Plan For Learning Data Science in 2020 | Click Here
    • Practice: Lecture of Day03 and Day04 | Click Here
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  • Lab03 - Data Structures in Python (List, Dictionary)
    • [Explore Video 1 (imp)] Step By Step Playlist To Learn Data Science Through Kish Naik Channel Part 1 | Click Here
    • [Explore Video 2 (imp)] Step By Step Playlist To Learn Data Science Through Kish Naik Channel Part 2 | Click Here
    • Practice: Lecture of Day05 and Day06 | Click Here
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  • Lab04 - Data Structures in Python (Tuple, Sets)
    • [Explore] Learn Neural Network and Deep Learning with code and Videos (By Prof Jeff Heaton) | Video  Code   
    • Practice: Lecture of Day07 and Day08 | Click Here
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  • Lab05 - File Handling, Use of Lambda, Command-line arguments and Call External Commands
    • [Explore (imp)] Student Projects @ Stanford University | Click Here
    • [Explore (imp)] Student Projects @ MIT  | Click Here
    • Practice: Lecture of Day09 and Day10 | Click Here
    • Practice: How to read a file in Google Colab | Link1 Link2
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  • Lab06 - OOPs in Python
    • [Explore (imp)] Student Projects @ LeadingIndia.ai  | Click Here
    • [Explore (imp)] Research Projects @ LeadingIndia.ai  | Click Here
    • [Explore (imp)] Resources @ LeadingIndia.ai  | Click Here
    • Practice: Lecture of Day11 and Day12 | Click Here
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  • Lab07 - Data Manipulation using Pandas
    • [Explore Video (imp)] Data Manipulation using Pandas by Kish Naik | Part1  Part2  Part3
    • Practice: Lecture of Day13, Day14 and Day15 | Click Here
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  • Lab08 - Data Visualization using Matplotlib and Seaborn
    • [Explore (imp)] PyPi.org: Python packages for research | Click Here
    • [Explore (imp)] Two minutes Papers  | Click Here
    • [Explore (imp)] Papers With Code | Click Here
    • Practice: Lecture of Day16 and Day17 | Click Here
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  • Lab09 - Correlation, Regression, Least Sum of Square, Multivariate Regression
    • [Explore (imp)] User Guide for Machine Learning @scikit-learn | Click Here
    • Practice: Lecture of Day18 and Day19 | Click Here
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  • Lab10 - Exploratory Data Analysis (EDA)
    • [Video (imp)] Pandas Visual Analysis: Perform Exploratory Data Analysis In A Single Line Of Code | Click Here
    • [Video (imp)] D-Tale: The Best Library To Perform Exploratory Data Analysis Using Single Line Of Code | Click Here
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  • Lab11 - Feature Selection
    • [Video (imp)] Tutorial 1: How To Drop Constant Features Using Variance Threshold | Click Here
    • [Video (imp)] Tutorial 2: How To Drop Features Using Pearson Correlation | Click Here
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05 - Assingment
3. Assingments
Evaluation Criteria: Multiplying Factor (MF)
      Assignment_Marks = 10          # Lets assume
      if (Assignment_Submitted_Within_Due_Date):
                   MF = 1
      else:
                  MF = 1 - abs(Submission_Date - Due_Date)/10
 
      You_Get_the_Marks_From = Assignment_Marks * MF
5.1 A01 - Basics of Python | Due Date: 23 Aug 2020 | 23:59:59 | Assignment Link | Submission Link
5.2 A02 - File Processing | Due Date: 23 Aug 2020 | 23:59:59 | Assignment Link | Submission Link
5.3 A03 - Video Processing using OpenCV | Due Date: 06 Sep 2020 | 23:59:59 | Assignment Link | Submission Link
5.4 A04 - Merging of Results | Due Date: 20 Sep 2020 | 23:59:59 | Assignment Link | Submission Link
5.5 A05 - Feature Extraction | Due Date: 27 Sep 2020 | 23:59:59 | Assignment Link | Submission Link
5.6 A06 - TOPSIS | Due Date: 16 Nov 2020 | 23:59:59 | Assignment Link | Submission Link
5.7 A07 - Data Analytics and Visualization using Google Data Studio
​5.8 A08 - Data Analytics using Tableau
5.9 A09 - Processing of Time Series Data
5.10 A10 - Coursera Project Certification
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06 - Books
4. Books
6.1 Python Data Science Handbook | Click Here
6.2 Book 1
6.3 Book 2
07 - Projects
5. Projects
7.1 DNA Sequencing Classifier using Machine Learning (Notebook is available in the description) | Click Here
7.2 Colour Detection | Click Here
7.3 Titanic data exploration and prediction using Machine Learning | Click Here
7.4 Tumer Analysis (by Kritika Aggarwal) | Click Here
7.5 How To Train Deep Learning Models In Google Colab- Must For Everyone | Click Here
7.6 Handling Imbalanced Datasets   SMOTE Technique | Click Here
7.7 Tumer Analysis (by Kritika Aggarwal) | Click Here
08 - Self Learning Resources
6. Self Learning Resources
8.1 Explore and subscribe to Youtube Channels
8.2 Data Science Projects playlist | Click Here
8.3 Free Coursera Courses for Thapar Students | Click Here and Join with *@thapar.edu. Click on Catalog.
8.4 Learn NumPy in a very easy way (By Simran, BE, 4th Yr) | Click Here
8.5 Learn Neural Network and Deep Learning with code and Videos (By Prof Jeff Heaton) | Video  Code

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09 - Resource for Research Paper
7. Resource for Research Paper
9.1 Paper With Code | Click Here
9.2 Two Minutes Papers | Click Here
​9.3 For Research Papers

Search using DOI (Digital Object Identifier) | Example (Search for): 10.1016/j.bbapap.2014.07.010

Search using title | Example (Search for): "Quality assessment of modelled protein structure using"

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9.4 For Books
​9.5 For Thesis
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