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#Exercise #Questions #Solution #MODULE8
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👇Case study: Inferential Statistics👇
Annova-Chi squre

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#Exercise #Questions #Solution #MODULE9
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👇Feature Engineering:👇
know your data

Exercises / Case Studies

Module 2 - Introduction to Python
2.1 Introduction to Python (To Do Template)
2.2 Numpy Template
2.3 Matplotlib question
2.4 Dictionaries and Pandas Question
2.5 Comparison operators
Q= https://t.me/Machine_Learning_Deep_Learning/290
Ans:https://t.me/Machine_Learning_Deep_Learning/296

Module 3 - Pandas
3.1 Introducing DataFrames Template
3.2 Summary Statistics Template
3.4 CH - 3 Pandas (Template)
3.5 CH - 4 Visualizing Data frames Template
Q=https://t.me/Machine_Learning_Deep_Learning/302
Ans=https://t.me/Machine_Learning_Deep_Learning/307

Module 4 - Merging Data Frames with Pandas
4.1 Pandas Ch1 template
4.2 CH 2 Pandas Template
4.3 Merging DataFrame
Q=https://t.me/Machine_Learning_Deep_Learning/313
Ans=https://t.me/Machine_Learning_Deep_Learning/317

Module 5 - Introduction to Data Visualisation Using Matplotlib
5.5 MatplotLib case study
https://t.me/Machine_Learning_Deep_Learning/321

Module 6 - Data Visualization with Seaborn
6.0 Matplot and Seaborn Case Study
https://t.me/Machine_Learning_Deep_Learning/327

Module 7 - Descriptive Statistics with Python
7.2 DESCRIPTIVE STATS CASE STUDY
https://t.me/Machine_Learning_Deep_Learning/332

Module 8 - Inferential Statistics with Python
8.2 Inferential statistics (Annova-Chi square Case Study)
https://t.me/Machine_Learning_Deep_Learning/337

Module 9 - Feature Engineering
9.1 Decodr- Feature Engineering for Machine Learning in Python
https://t.me/Machine_Learning_Deep_Learning/341

Module 10 - Machine Learning for Everyone
(Nothing here)

Self Paced videos
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—— —— #MODULE12 ————
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👇Tree Based Models in python👇

1. What is Decision Tree Classification

2. Implement Decision Tree Classification

3. What is Decision Tree Regression

4. Implement Decision Tree Regression