When using machine learning, we need to be able to trust our models and the predictions they make. We may use sample data to train our models. This sample data may make certain assumptions about a population.

Yet, if we have no way to test whether the assumptions represent a whole population or not, we will struggle to tell if our results are due to any statistical significance or just chance.

Statistical vs. Machine learning Hypothesis

Even though most of the concepts we will cover in this article are predominantly statistical, it is important to understand how the term hypothesis is perceived from either a…


In a world where nearly all manual tasks are being automated, the definition of manual is changing. Machine Learning algorithms can help computers play chess, perform surgeries, and get smarter and more personal.

We are living in an era of constant technological progress, and looking at how computing has advanced over the years, we can predict what’s to come in the days ahead.

One of the main features of this revolution that stands out is how computing tools and techniques have been democratized. In the past five years, data scientists have built sophisticated data-crunching machines by seamlessly executing advanced techniques…


I think there are lots of people who might be a little bit confuse or we can say may have not clear between Statistic and machine learning.
Even I was aware of machine learning but I was not clear much about statistics. I have started reading about statistics and here I got to know what exactly is statistics and machine learning.

Statistics: The statistics way of thinking typically says you formulate the problem then you get the data to solve that problem. A statistical model, on the other hand, is a subfield of mathematics. …


Hi Guys, My name is Sunil and I’m from India. While I was in college, I have no idea what I will do after doing graduation. I was looking for a Campus job but due to fewer marks in academics most of the time, I was not eligible for a company. While last year I get knew about the Data Science field and it looked quite an interesting Field. Basically Doing graduation in Computer Engineering I was never interested in a software developer.

I was started learning data science but it was very hard as there was no mentor who…


What is Data Cleaning and Why do we need it?

In the data science field, as we know most of the time we spend on data cleaning. So today I will give some suggestions and methods while cleaning data what precautions should we have to take while Data Cleaning.

First, We will know what is Data Cleaning? We will define in a simple manner that, Data Cleaning is the process of detecting incomplete, incorrect, inaccurate, or irrelevant parts of the data and then replacing, modifying, or deleting the dirty data. Data cleaning is also called Data Cleansing. So don’t be…

Sunil Prajapati

Data Science enthusiast | Machine Learning | Deep Learning | Data Analyst | Software Support Engineer

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