Day 11 | Artificial Intelligence and Machine Learning: Task 1

4 years ago Rajkumar Dindor Leave a Comment on Day 11 | Artificial Intelligence and Machine Learning: Task 1
Save
Day 11 | Artificial Intelligence and Machine Learning: Task 1

Information

Date: 05.07.2020

Task 1

Title: Linear Regression in Python for machine learning.

Software used: Python 2.7, Jupyter Notebook, Pandas, Scikit-learn, Pickle, Numpy, GhCpython,

MS Excel.

Tools Used: Python 2.7, Jupyter Notebook, Scikit-learn, Pickle, Numpy, GhCpython Script.

The session was to learn scripting in Python and understand fundamentals of Machine Learning. The data used was from the project used in the previous day session. Analysis was done through linear regression method in python using scikit learn interface.

 

Importing interfaces; numpy,pandas,scikit-learn, pickle and data from excel file in jupyter notebook. Pickle is used to convert input data into binary form and vice versa for output data.

Day 11 | Artificial Intelligence and Machine Learning: Task 1
Importing interfaces; numpy,pandas,scikit-learn, pickle and data from excel file in jupyter notebook. Pickle is used to convert input data into binary form and vice versa for output data.
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Extracting objects in ’0’ row from excel file and returning Data values into individual rows.
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Diagram showing logistics of data when split in sets as testing set and training set in Python ML. The mathematical expression is the approach that ML runs through when a linear regression method takes place.
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Data being split into train sets and test sets. ‘predict’ returns the learned object in the array.
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Regression being done for the train set and test set for ‘absolute mean error’, ‘mean square error’ and ‘root mean square error’.
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Values being added to the Cpython script from excel.
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Final outcome from GhCpython in grasshopper.

Images

Day 11 | Artificial Intelligence and Machine Learning: Task 1
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Day 11 | Artificial Intelligence and Machine Learning: Task 1
Day 11 | Artificial Intelligence and Machine Learning: Task 1

Author

Rajkumar Dindor

Rajkumar Dindor is an architect graduated from Faculty of Architecture, CEPT University, India. He has been teaching as a Visiting Faculty at CEPT University since 2018 and also runs his own architecture & design practice with his partner, Prachi Nagar, at Ahmedabad.

Leave a Reply