What Is Chi-square Goodness Of Fit Test? As a data science engineer, it’s imperative that the sample data set which you pick from the data is reliable, clean.

As a data science engineer, it’s imperative that the sample data set which you pick from the data is reliable, clean, and well tested for its usability in machine learning model building.

**So how do you do that?**

Well, we have multiple statistical techniques like descriptive statistics where we measure the data central value, how it is spread across the mean/median. Is it normally distributed or there is a skew in the data spread? Please refer to my previous article on the same for more clarity.

As the first thing we do is to visualize the data using various data visualization techniques to make some early sense of any data skewness or discrepancies, to identify any kind of relationship between data set variables.

Data has so much to say and we data engineer give it a voice to express and describe itself, using descriptive statistical techniques.

But to make any prediction or to infer something beyond the given data to find any hidden probability, we rely on inferential statistic techniques.

*Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population.*

machine-learning data-analysis data-science technology statistics data analysis

Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.

Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.

Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant

Statistics for Data Science and Machine Learning Engineer. I’ll try to teach you just enough to be dangerous, and pique your interest just enough that you’ll go off and learn more.

In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.