top of page

UCS654: Predictive Analytics using Statistics (Jan to June 24 - Even 2324)

Table of Content
Join WhatsApp Group | Click Here
Marking Scheme
  1. MST = 30 Marks*
  2. EST = 40 Marks*
  3. Sessionals = 30 marks*
01 - Lecture Resources
01 - Lecture Resources
​
  • Topic01 - Topsis - Multiple Criteria Decision Making  |  Link
  • Topic02 - Sampaling | Link
  • Topic03 - Distribution | Link
  • Topic04 - Machine Learning using Pycaret | Link
  • Topic05 - Data Generation using Modelling and Simulation for Machine Learning | Link
  • Topic06 - Association Mining - Apriori | Link
  • Topic07 - Association Mining - ECLAT | Link
  • Topic08 - Multi-Threading using Python | Link
  • Topic09 - Hypothesis Testing and Parameter Estimation | Link
  • Topic10 - Parameter Optimization | Link
  • Topic11 - Non Liner Modelling | Link
  • Topic12 - Measuring Data Similarity and Dissimilarity | Link
  • Topic13 - NA | Link
02 - Labs Experiments
02 - Labs Experiments - Guided Project & Kaggle
General Instructions
​
1. Guided Project (GP)
  • Step 1: Create a login with Thapar email id on Coursera (coursera.org).
  • Step 2: Complete the given below "Guided Project" and submit the "Compeletion Certificate" link.
  • Step 3: Explore Sample Certificate | Click Here
  • Step 4: Explore all "Guided Projects" on Coursera | Click Here
​
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
​
​
​
​
​
​
​
​
​
​
​
  • Lab11
03 - Assignments
03 - Assignments
  • Assignment01 - Topsis
  • Assignment02 - Sampling
  • Assignment03 - Topsis for Pretrained Models
  • Assignment04 - Clustering
  • Assignment05 - Mashup
  • Assignment06 - Parameter Estimation
  • Assignment07 - Multi Threading
  • Assignment08 - Parameter Optimization of SVM
Assignment01 - Marks Analysis | 05 Marks | Due Date: 30 Jan 2022 | 23:59:59 | Assignment Link | Submission Link
Assignent02 - Feature Extraction | 05 Marks | Due Date: 06 Feb 2022 | 23:59:59 | Assignment Link | Submission Link
Assignment03 - Classification | 05 Marks | Due Date: 20 Feb 2022 | 23:59:59 | Assignment Link | Submission Link
​​Assignment05 - Google Data Studio | 05 Marks | Due Date: 10 March 2022 | 23:59:59 | Assignment Link | Submission Link
04-KaggleHack
04 - Kaggle Hack
  • Kaggle Hack 01 - Google – AI Assistants for Data Tasks with Gemma | Click Here to participate
    • Due Date: 14 April 2024
    • Maximum Team Size: 5
    • Register Your Team - Click Here
    • Important | Team Naming Convention on Kaggle:
      • Team Name Format: <Thapar>_<TeamLeaderName><TeamLeaderRollNo>
      • Example: Thapar_PSRana_14567890
    • Marking Scheme: Based on the final ranking on the leaderboard

      • Rank in Top 50 = A grade in the subject (All team members will get A grade)

      • Rank between 51 - 100 = 5 marks

      • Rank between 101 - 150 = 4 marks

      • Rank between 151 - 200 = 3 marks

      • Rank between 201 - 400 = 2 marks

      • Rank above 400 / No submission = 0 Marks

    • Rule: No Rule

(Jo

  • Kaggle Hack 02 - Due Date: 30 Jan 2024 | 07:59:59 | Click Here to participatekar

na hai kar lo)

bottom of page