Machine Learning | Train Test Split in Cross Validation using Pandas and Numpy

Machine Learning | Train Test Split in Cross Validation using Pandas and Numpy
How to do Train Test Split using

2. pandas
3. numpy
4. train test split in a sequential order
'''

Method No 2 using Pandas
import pandas as pd
import numpy as np

X, y = make_blobs(n_samples=10, random_state=1)
df = pd.DataFrame(X)

train train Split -- 60 : 40

train train Split -- 70 : 30

train validate test split -- 60 : 20 : 20
int(0.8*len(df))])

train validate test split -- 50 : 30 : 20
int(0.8*len(df))])

All Playlist of this youtube channel
====================================

1. Data Preprocessing in Machine Learning

2. Confusion Matrix in Machine Learning, ML, AI

3. Anaconda, Python Installation, Spyder, Jupyter Notebook, PyCharm, Graphviz

4. Cross Validation, Sampling, train test split in Machine Learning

5. Drop and Delete Operations in Python Pandas

6. Matrices and Vectors with python

7. Detect Outliers in Machine Learning

8. TimeSeries preprocessing in Machine Learning

9. Handling Missing Values in Machine Learning

10. Dummy Encoding Encoding in Machine Learning

11. Data Visualisation with Python, Seaborn, Matplotlib

12. Feature Scaling in Machine Learning

13. Python 3 basics for Beginner

14. Statistics with Python

15. Sklearn Scikit Learn Machine Learning

16. Python Pandas Dataframe Operations

17. Linear Regression, Supervised Machine Learning

18 Interiew Questions

19. Jupyter Notebook Operations