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UCS513: Machine Learning (July to Dec 24 - ODD 2425)

Table of Content
Join WhatsApp Group | Click Here
Marking Scheme
  1. MST = 35 Marks
  2. EST = 35 Marks
  3. Sessionals = 30 marks
01 - Lecture Resources
01 - Lecture Resources
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  • Topic01 - Topsis - Multiple Criteria Decision Making  |  Link
  • Topic02 - Machine Learning using Pycaret | Link
  • Topic03 - Box Plot and Outlier Detection | Link
  • Topic04 - Data Generation using Modelling and Simulation for Machine Learning | Link
  • Topic05 - Parameter Optimization | Link
  • Topic06 - Ensemble Technique | Link
  • Topic07 - Association Mining - Apriori | Link
  • Topic08 - Sampaling | Link
  • Topic09 - Multi-Threading using Python | Link
  • Topic010 - Measuring Data Similarity and Dissimilarity | Link
02 - Labs Experiments
02 - Labs Experiments - Guided Project & Kaggle
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  • Lab01 | 01-08-2024
    • Explore pypi.org
    • Search the below text
      • Convert audio to text
      • Download google images
      • Convert video to audio
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  • Lab02 | 08-08-2024
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03 - Assignments
03 - Assignments
04-KaggleHack
04 - Kaggle Hack
1. Be a Grand Master or Master in Kaggle and get A Grade

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2. Solve Kaggle Problems | Kaggle Resources
  • Getting started with Kaggle by Mr. Raghav Garg, Mr. Aadil Garg, Mr. Pratham Garg | Click Here
  • Kaggle Resources by Mr. Eishkaran Singh | Click Here
  • Kaggle Grand Master Talks
T-1  |  T-2  |  T-3  |  T-4  |  T-5  |  T-6  |  T-7  |  T-8  |  T-9  |  T-10
  • Kaggle notebooks
    • Latest Playground Series Basic's Notebook for Beginners | Click Here
    • Latest Playground Series Advanced Approach | Click Here
    • XGB HyperParameter Tuning Notebook | Click Here
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