A Mathematics student turned Data Scientist. I am an aspiring data scientist who aims at learning all the necessary concepts in Data Science in detail. I am passionate about Data Science knowing data manipulation, data visualization, data analysis, EDA, Machine Learning, etc which will help to find valuable insights from the data.
A case study focuses to give you an idea of applying Exploratory Data Analysis (EDA) in a real business scenario.
Understand Linear Regression, from basics to advanced concepts like best fit line, cost function, gradient descent, R-squared, overfitting, and hands-on coding.
Statistics provides tools and methods to seek out structure and to offer deeper data insights. Let's learn statistics for machine learning.
Mathematics is a subject that is required in almost any field. In this article, we will look into the Mathematics For Machine Learning.
Pandas is an open-source python library generally used for data manipulation and data analysis. Here, we will see a hands-on guide on pandas.
NumPy is a Python library widely used to handle arrays with arrays. It stands for numerical python. Here we present a hands on guide for it.
