**Pre- Processing**
Simple Imputer
https://colab.research.google.com/drive/1ClkeUzwMF6gYFNOmWqVE8d3VObv0rvxw#scrollTo=7_hxHGmiDUf8
https://drive.google.com/file/d/1Y19UQb8KIrzrpaXUrjdP_KC5l_AxXwaq/view?usp=drive_link, https://drive.google.com/file/d/10pqCe87E6ZGiZl7uBDVihz2YgEzlTVk8/view?usp=drive_link, https://drive.google.com/file/d/1HWDwlNwYmXG-WV89igxF_lzDgkhMFYwd/view?usp=drive_link, https://drive.google.com/file/d/1o0UqVw3-On-E-zIXT2I79OmMlId43B1U/view?usp=drive_link, https://drive.google.com/file/d/1-1DVQq9LI1f-vI5KmkcDnkS3SxVRHlWt/view?usp=drive_link, https://drive.google.com/file/d/1kEqWeUy8LnEA8FEL1gTdXs-fgD831xil/view?usp=drive_link, https://drive.google.com/file/d/1J4XI1CKasjNbXRHmoUzjQOqUNNbeNNDg/view?usp=drive_link, https://drive.google.com/file/d/1EPBHXWLBeLCZWY710PKwW3w2IGzkjxXo/view?usp=drive_link
##Material: ================================ 1. Linear Regression https://docs.google.com/presentation/d/1qWPLHYr99Xkm3uU5s9bst30L0kKU3PHj/edit#slide=id.p100
2. Multi Linear Regression
https://www.statology.org/multiple-linear-regression-by-hand/
3. POLY Regression
https://colab.research.google.com/drive/19r96EfLFmIAPya7ZTNaYJ6-qSDvRBST4#scrollTo=j6tyRYL7yJ4Q
==================================
###SVM:
1. L-SVM- https://github.com/ksarvakar/DSML-2023/blob/main/LSVM.pdf
2. NL-SVM- https://github.com/ksarvakar/DSML-2023/blob/main/NL-SVM.pdf
KNN- MATERIAL https://docs.google.com/document/d/1xhUJ9mPvi8HWieQITMp_hXGbPWNPJqAIOvX3KuIqRo0/edit?hgd=1
##Material:
1. PPT- https://docs.google.com/presentation/d/1hwZnXLxUVOoVAK1PB22h70XQab36KTZa/edit#slide=id.p53
2. Online Apriori- https://athena.ecs.csus.edu/~mei/associationcw/Algorithms/Apriori.html
=====
###LIFT METHOD:
1. https://www.youtube.com/watch?v=9_kT7GaQwAc
==========
K-MEANS
**Code:** https://colab.research.google.com/drive/1AnBNdC0QBUzKsyQed45tqbJLATx0hR1P#scrollTo=WW--Xpml6R1s
**dataset:** https://www.kaggle.com/datasets/ksarvakar/mall-customers
**Video:** https://www.youtube.com/watch?v=Kz1kV1zbJ0Q&list=PLLX0OlcGRiD6rAbO6cTwaxNzDqQoZ427-&index=13
+++++++++++++++++++
DBSCAN Clustering Algorithm Solved Numerical Example in Machine Learning Data Mining Mahesh Huddar
PCA- LDA - MATERIAL
https://drive.google.com/drive/u/0/folders/1sxbd_hliEdiG2iIt3GYLWDn7XlYweSc-
###Assignment Links:
###Assignment -1.1 label encoding, One Hot Encoder
https://docs.google.com/document/d/1tkyWY7QhVFYPAEBnxd31pXYZJeo6pnBW/edit
###Assignment-2 Data Pre-processing
https://docs.google.com/document/d/1Xay7Gv7XeMq0MwsvIwpOL2tWf8Pfy0Xf/edit
###Assignment 3 Normalization
https://docs.google.com/document/d/15XWx3v5kgI_18cfKVJZc7UzowotK-gSm/edit
###Assignment - 4 Association rule
https://docs.google.com/document/d/19fTivylDJcJRAYUrds1jv0txxT69AFbA/edit
###SVM:
https://docs.google.com/document/d/1iJETP5U2ggAELFtPg1GB32xVISbuDoKkbBBC1ceSPcc/edit
=================================================================================================================
Case Study:
-
Auto-mobile price prediction using AZURE-ML https://studio.azureml.net/
Video:
- https://www.youtube.com/watch?v=Gny_Xb_T0eQ
- Predicting housing pricing in California using AzureML https://www.youtube.com/watch?v=TNEhb5u7X2E
Using Code: https://medium.com/cs-334-data-science/predicting-housing-prices-in-california-331334f53ad7
Document: https://learn.microsoft.com/en-us/previous-versions/azure/machine-learning/classic/create-experiment
==============================================
Practical:
Index- Practical-1: Aim: To build and fine-tune a Support Vector Machine (SVM) model for predicting heart disease with an accuracy of at least 85% using the dataset provided in the Kaggle notebook.
Market Basket Analysis (Apriori) in Python
- https://www.kaggle.com/code/ksarvakar/notebook04ddbfaaa6
- https://www.kaggle.com/code/ksarvakar/how-to-solve-the-apriori-algorithm-in-a-simple-way
- https://colab.research.google.com/drive/19oz_jjjAS3rFffx3uNZCwzFP_Gy3AF3s#scrollTo=bw35MisP_nit
SVM 1. https://www.kaggle.com/code/ksarvakar/support-vector-machines-predicting-heart-disease
KNN 1. https://www.kaggle.com/code/ksarvakar/predicting-heart-disease-with-knn-and-svm
=====================================
Jiawei Han, Micheline Kamber and Jian Pei
Data Mining: Concepts and Techniques, 3rd ed.
The Morgan Kaufmann Series in Data Management Systems Morgan Kaufmann Publishers, July 2011. ISBN 978-0123814791
Slides in PowerPoint https://hanj.cs.illinois.edu/bk3/bk3_slidesindex.htm
Certification Courses:
1. https://www.kaggle.com/learn/pandas
2. https://www.kaggle.com/code/sanikamal/data-visualization-using-matplotlib/notebook
3. https://www.kaggle.com/code/saurav9786/matplot-tutorial-for-everyone/notebook
4. https://www.kaggle.com/code/prashant111/matplotlib-tutorial-for-beginners/notebook
5. https://www.kaggle.com/learn/data-visualization
====================================
6. https://www.kaggle.com/learn/data-cleaning
7. https://www.kaggle.com/code/residentmario/creating-reading-and-writing
=====================================
8. https://www.javatpoint.com/data-preprocessing-machine-learning
=====================================
9. https://www.w3schools.com/python/pandas/default.asp
10. https://www.w3schools.com/python/matplotlib_intro.asp
11. https://www.w3schools.com/python/scipy/scipy_getting_started.php
=====================================
Cognitive Class Certificate Course
12. https://apps.cognitiveclass.ai/learning/course/course-v1:BigDataUniversity+DS0101EN+v1/home
13. https://courses.cognitiveclass.ai/courses/course-v1:CognitiveClass+PY0101EN+v3/progress
14. https://apps.cognitiveclass.ai/learning/course/course-v1:CognitiveClass+DV0101EN+v2
15. https://cognitiveclass.ai/learn/data-science-with-python
=====================================
Google CO-LAB Files: 1.https://drive.google.com/drive/folders/12pwViRv_088P2MT-LZm1q-wGyeDToYyU
DSML-2021 - KETAN PERSONAL.
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