Mathematics for data science: Linear Algebra Part-1
Introduction Linear algebra is the bedrock of data science and machine learning. Linear algebra provides mathematical insights to solve equations we use to build models. [continue reading..]
An introduction to data science
Introduction What motivates people to get into data science fields? Why do people want to become a data scientist? Actually, if you want to find [continue reading..]
Artificial Neural Network( The basic idea behind machine’s brain)
“Machine learning involves in adaptive mechanisms that enable computers to learn from experience, learn by examples and learn by analogy. Learning capabilities can improve the [continue reading..]
Variables & Data Types in python
Introduction Variables are somethings which store data. It reserved memory locations to store data. We can understand it by a different way like in mathematics [continue reading..]
An Introduction to Data visualization.
Introduction In the era of big data, we are facing a large amount of data on the daily basis and these data are very important [continue reading..]
Top technology trends that will dominate 2018
Regardless of whether you’re a diehard tech fanatic(means a type of people like me who look forward to the tech development and trends that lie ahead) [continue reading..]
An Introduction to Tensorflow
Introduction Tensorflow is an open source software library for numerical computation that enables machine learning practitioners more data-intensive computing. It also provides some robust widely [continue reading..]
Optimization through Gradient Descent
Optimization refers to the task of either maximizing or minimizing some function f(x) by altering x. The function we want to minimize or maximize is [continue reading..]
Simplified Bayes’s Theorem
Bayes’s theorem is the fundamental concept behind Bayesian statistics and there are several machine learning and deep learning algorithm depends upon Bayes’s theorem like Naive [continue reading..]
Linear Regression from scratch
[table id=1 /] These all questions implies the answer would be quantitative or continuous in nature. Linear regression is the fundamental topic for the predicting [continue reading..]