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DataScience_Notebook

The best way to learn is by hands-on practice. This notebook contains all the fundamental and basics code for Data Science, Machine Learning and Deep Learning. I will keep incrementally adding to this repository as I progress in my journey.

Tabs:

Linear Regression :

Day 1 : Simple Linear Regression 

Day 2 : Multiple Linear Regression

Day 3 : Linear Regression with Sklearn

Day 4 : Real Life Example using Sklearn

Logistic Regression :

Day 5 : Logistic Regression

KMeans Clustering :

Day 6 : KMeans Clustering 

Day 7 : Clustering Exercises <br>

Mathematics :

Day 8 : Linear Algebra

Deep Learning :

Day 9 : Basic Neural Network

Day 10 : TensorFlow 

Day 11 : MNIST Deep Neural Network

Day 12 : Business Case Model - AudioBooks Example

Case Study :

Day 13 : Preprocessing Module for Absenteeism Data

Day 14 : Logistic Regression Model for Absenteeism Preprocessed Data

References :

Data Science : https://www.udemy.com/course/the-data-science-course-complete-data-science-bootcamp/

Machine Learning : https://www.udemy.com/course/machinelearning/