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2.1 Introduction to Python Libraries.html
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1 - Introduction to Machine Learning
10 - Support Vector Machines
11 - K Nearest Neighbors for Classification and Regression
12 - Decision Tree Classifier Algorithm
13 - Random Forest Classifier Algorithm
14 - Naive Bayes Algorithm
15 - Resources
Notebooks
16 - KMeans Clustering
2 - Types of Machine Learning
3 - The Machine Learning Pipeline
11 - Important Libraries in Python.html
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1 - Introduction
Logistic Regression in Python
Data Files
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Presentation
10 - Knearest Neighbors Classifier
11 - Understanding The Results
12 - Appendix 1 Linear Regression In Python
ML Practical task 3
ML Task 1
ML Task 2
13 - Congratulations About Your Certificate
2 - Introduction To Machine Learning
3 - Basics Of Statistics
4 - Setting Up Python And Jupyter Notebook
5 - Important Python Libraries
24 - Python File For Additional Practice.html
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307 B
25 - About The Upcoming Role Play.html
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1.1 KB
6 - Data Preprocessing
30 - Project Exercise 1.html
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33 - Project Exercise 2.html
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36 - Project Exercise 3.html
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39 - Project Exercise 4.html
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43 - Project Exercise 5.html
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46 - Project Exercise 6.html
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7 - Classification Models
51 - Project Exercise 7.html
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307 B
55 - Project Exercise 8.html
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60 - Project Exercise 9.html
HTML
204 B
8 - Linear Discriminant Analysis Lda
63 - Project Exercise 10.html
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204 B
9 - Testtrain Split
65 - More About Testtrain Split.html
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512 B
67 - Project Exercise 11.html
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1 - Welcome Python Fundamentals for Real Estate Bootcamp
2 - Getting Started with Python
3 - Python Building Blocks
4 - Python Packages for Real Estate
34. Introduction to Python Libraries.html
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2.1 Introduction to Python Libraries.html
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