Contributors: Bhanu Shahi, Vaideswar Reddy & Prashant Jha

ML use cases in Logistics

Logistics refers to the overall process of managing how resources are acquired, stored, and transported to their final destination.

The term logistics is now used widely in the business sector to refer to how resources are handled and moved along the supply chain. Companies today need smart, flexible, and proactive supply chain decision-making solutions to cater to the dynamic demands of the market.

How to ensure efficient logistics management?

This is an open question for many suppliers, distributors, manufacturers, and retailers.

Machine learning holds the answer to many well-known as well as…


Statistics is all about data but data alone is not interesting. It is the interpretation of the data that we are interested in…

The hypothesis test is one of the ways to do this interpretation.

Hypothesis originates from the Greek word hupo (under) and thesis (placing).

  • Using Hypothesis Testing, we try to interpret or draw conclusions about the population using sample data.
  • A Hypothesis Test evaluates two mutually exclusive statements about a population to determine which statement is best supported by the sample data.
  • A hypothesis is a tentative insight into the natural world; a concept that is not yet…


If you want to be an anomaly, you have to start acting like one…

Introduction

In this blog, we are going to understand what an anomaly is and what are some basic anomaly detection techniques.

So, let’s start with the understanding of anomaly.

An anomaly is something that deviates from what is standard, normal, or expected. We often have to check for anomalies while doing data analysis.

The main goal of Anomaly Detection analysis is to identify the observations that do not adhere to general patterns considered as normal behavior.

Anomaly detection is often applied on unlabeled data which is known…


A special kind of beauty exists which is born in language, of language, and for language.

Data Scientists work with tons of data, and many times that data includes natural languages like text and speech. That text is usually quite similar to the natural language that we use in our day-to-day life. They have to convert those natural languages into machine-readable forms.

In this blog, we are going to see some common NLP techniques, with the help of which we can begin performing analysis and building models from textual data.

What is Natural Language?

  • From data prospectives, Natural Language refers to speech and text.


“If we teach today as we taught yesterday, we rob our children of tomorrow.” — John Dewey

Data Science has spread its branches through several fields of the world today. It has emerged out as a global phenomenon that has revolutionized industries and has increased their performances substantially.

In this blog, I am going to explain some applications of data science in the Ed Tech industry.

“Education is the most powerful weapon that we can use to change the world” — Nelson Mandela

So let’s start with the understanding of the term Ed Tech.

What Is EdTech?

EdTech is a…


“A baby learns to crawl, walk and then run. We are in the crawling stage when it comes to applying machine learning.” ~Dave Waters

We are living in a world full of Humans and Machines. We the humans are learning and evolving from our past experiences for billions of years, on the other hand, the era of machines and robots has just begun.

In today’s world, these machines or robots need to be instructed to perform, but what if machines started to learn on their own and this is where machine learning comes into the picture.

In this blog, we…

Bhanu Shahi

Aspiring Data Scientist | Machine Learning | NLP | Time Series | Python, Tableau & SQLExpert | Storyteller | Blogger | Data Science Trainee at AlmaBetter

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