machine_learning

This repositoy contains all the jupyter notebooks used for Machine Learning.

Regression

This folder contains all the python notebook used to learn regression. The topic covered are:

1. Linear Regression:
   Fuel Consumption example is used to understand linear regression. Notebook - Lab_01_Simple-Linear-Regression.ipynb
2. Multiple Linear Regression
   Fuel Consumption example is used to understand multiple linear regression. Notebook - Lab_02_Mulitple-Linear-Regression.ipynb
3. Polynomial Regression
   Fuel Consumption example is used to understand polynomial linear regression. Notebook - Lab_03_Polynomial-Regression.ipynb
4. Non Linear Regression
   China_gdp example is used to understand non linear regression. Notebook - Lab_04_NoneLinearRegression.ipynb
5. K-Nearest Neighbors
   Telecommunications dataset example is used to understand this concept. Notebook - Lab_05_K-Nearest-neighbors-CustCat.ipynb
6. Decision Trees
   classification algorithm to build a model from historical data of patients, and their response to different medications
   Notebook - Lab_06_Decision-Trees-drug.ipynb

Clustering

This folder contains all the python notebook used to learn clustering. The topic covered are:

1. K-Means:
   Customer Segmentation example is used to understand the K-Means clustering. Notebook - K-Means-Customer-Seg.ipynb
2. Hierarchical Clustering
   Clustering on Vehicle dataset using Hierarchical Clustering. Notebook - Hierarchical-Cars.ipynb
3. Density-based spatial clustering
   Weather Station Clustering using DBSCAN & scikit-learn. Notebook - dbscan_basics.ipynb

projects:

breast_cancer_detection kaggle data link: https://www.kaggle.com/uciml/breast-cancer-wisconsin-data

Resource:
NPTEL: https://nptel.ac.in/courses/106106139/
Coursera: https://www.coursera.org/learn/machine-learning-with-python
cognitiveclass.ai: https://cognitiveclass.ai/courses/machine-learning-with-python
Notes:
Machine Learning with Python_week2.pdf
Machine Learning with Python_week4.pdf