Infographic Note on steps to perform Count , filter , group and aggregate numerical values over a dataset using Numpy and Pandas in Python using Jupyter Notebook IDE

 

Infographic Note on steps to formulate and perform a Hypothesis Test using Numpy , Pandas and Scipy Libraries of Python

 

Infographic Short Note on Methods of Underfitting over a Statistical Model in Statistics and its applications in Machine Learning

 

Infographic Short Note on Alternative Hypothesis as a parameter for testing in Statistics and its applications of Machine Learning

 

Infographic Short Note on Null Hypothesis as a parameter for testing in Statistics and its applications of Machine Learning

 

Infographic Short Note on the concept of Level of Significance which is used to determine acceptance of a Statistical Hypothesis with applications over Machine Learning

 

Infographic Short Note on Type-1 Errors in Statistics and applications of Machine Learning

 

Infographic Short Note on type of Errors in Statistics and applications of Machine Learning

 

Infographic Short Note on Concept learning for a Search Problem over any Hypothesis space in Machine Learning

 

Infographic Short Note on Inductive learning Algorithms as a Hypothesis Problem involving Machine Learning

 

Infographic Short Note on ordering of a Hypothesis Problem involving Machine Learning

 

Infographic Short Note on Notation of More_general_than and More_specific_than relation of a Hypothesis Problem involving Machine Learning

 

Infographic Short Note on Ordering of Hypothesis in Statistics and its core concept Problem used in Machine Learning

 

Infographic Short Note on Notation of a Hypothesis for a Concept Learning Task in Machine Learning

 

Representation of a Normal Hypothesis Equation for Regressin taking a matrix and inverse of a matrix and a multiplicable vector - short note

 

Derivative of a Cost-Function term in a regression function - small note of formulation and procedure to formulate derivative expression

 

Basic Codes on Octave for Statistical Calculations on Matrices , Vectors

 

Notes on Matrices , Properties of Matrices , Inverse Matrix and Transpose of a Matrix , Regression , Scenarios on Regression , Representation of Hypothesis Equation , Gradient Descent , Cost Function

 

Short description of Gradient Descent Algorithm for checking convergence of hypothesis and cost functions - short notes with formula

 

Notes on - Linear Regression with one Variable with Cost Function of sample data points with difference between a Hypothesis function and Cost Function