Opinion

Differences between their algorithms and job titles

Photo by Juliana Amorim on Unsplash [1].

Table of Contents

Introduction

There are several articles comparing data science and deep learning, but there is still some confusion on what is different between machine learning and deep learning, as well as what is different between the study of machine learning and the professional titles associated with machine learning. Is there a difference? What does each mean? In this article, we will outline the differences, as well as job title examples of each field. …


A unique approach to creating categorical time bins for your Machine Learning algorithms

Photo by Lukas Blazek on Unsplash [1].

Table of Contents

Introduction

One of the most difficult parts of data science modeling is utilizing time. Time can be used in a variety of ways. There is time-series-specific modeling, but you can also look at time in a different way. We will be looking into that way, which is converting time into a categorical variable(s). While the order will be stripped away after conversion, the cyclical property of time will still be able to be recognized by the machine learning algorithm you are using. For this example, we will be using the emerging algorithm, CatBoost, to correctly…


Opinion

Which option is best for you?

Photo by Vasily Koloda on Unsplash [1].

Table of Contents

Introduction

This article is intended for people who already have an undergraduate degree looking to switch to data science, or people who are interested in knowing the benefits of each education option. With data science, machine learning, artificial intelligence, and deep learning emerging as popular jobs in nearly any industry, graduate programs have emerged just as much to keep up with the demand. However, there is another option that may be more enticing for a variety of reasons, which is a certificate in data science. …


Opinion

How Data Scientists can aggregate their data

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Table of Contents

Introduction

Data scientists often learn Python first before learning SQL, and therefore SQL can either be overwhelming or just a different experience that is not preferred. When there are similar functions in both SQL and Python, it is important to understand which method is best to use. Ultimately, it will go down to preference, and, if you are a Python connoisseur, it might be more beneficial to use Python to group or aggregate your data. In order to know why Python would be better to use over SQL, we…


Opinion

Actionable advice for learning Data Science from nothing

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Table of Contents

Introduction

While there may be a few approaches out there to data science from scratch, I wanted to give my take on it, with the thought of what I would do differently in mind if I were to start over. In my case, I started from scratch, majoring in a field that was not data science, to begin with for my undergraduate degree. After I experienced that first career, I then decided on data science, and quickly learned and applied as…


Opinion

Examples of how to approach common machine learning algorithm problems

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Table of Contents

Introduction

If you are an established data scientist, you may have seen some of these use cases already, however, if you are fairly new, these use cases can allow you to practice a variety of data science concepts that can be further applied across multiple industries. Unfortunately, data science use cases are usually not well-developed so quickly at companies, and instead, the use case will build over several meetings depending on the requirements and expectations of the project. It is important to have a sense of general…


Opinion

A deep dive into the benefits of each tool

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Table of Contents

Introduction

Both of these tools are important to not only data scientists, but also to those in similar positions like data analytics and business intelligence. With that being said, when should data scientists specifically use pandas over SQL and vice versa? In some situations, you can get away with just using SQL, and some other times, pandas is much easier to use, especially for data scientists who focus on research in a Jupyter Notebook setting. Below, I will discuss when you should use SQL and when you should use pandas. …


Opinion

Machine Learning vs NLP vs Data Engineer vs Data Scientist, and what it means to be in each role

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Table of Contents

Introduction

When looking at data scientist salaries and data science roles, it became obvious that there are different, more specific facets within data science. These facets relate to unique job positions, specifically, machine learning operations, NLP, data engineering, and data science itself. Of course, there are even more specific positions than these, but these can give you a general summary of what to expect if you land a job in one of these positions. I wanted to pick these four roles, too, because they can be separated…


Opinion

Similarities and differences between these two popular tech roles

Photo by Christina @ wocintechchat.com on Unsplash [1].

Table of Contents

Introduction

Before the prominence of data science jobs came the field of business intelligence. Although they may have been previously very similar positions, as the two roles have become more popular, the roles have also become more defined. With that being said, it is still important to note that there can be quite a bit of overlap between these positions depending on where you end up working. I will be discussing the differences and similarities that I have seen from my own career, as well as from real job descriptions. …


Opinion

Communication is key…with other business skills and advice

Photo by Kelly Sikkema on Unsplash [1].

Table of Contents

Introduction

As data scientists or future data scientists, we might see some of the same skills expressed as important, which they are; however, I want to bring up five skills and/or pieces of advice that are unique, so hopefully you can benefit from these examples and apply them moving forward in your career. The skills below will cover working with stakeholders as well as some programming tips and advice. …

Matt Przybyla

Sr. Data Scientist. Top Writer in Technology and Education. Author - Towards Data Science. MS in Data Science - SMU.

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