Scikit-learn Tutorial: Machine Learning in Python

Scikit-learn is a free machine learning library for Python. It features various algorithms like support vector machine, random forests, and k-neighbours, and it also supports Python numerical and scientific libraries like NumPy and SciPy. In this tutorial we will learn how to easily apply Machine Learning with the help of the scikit-learn library, which was […]

How to Find an Entry-Level Job in Data Science

When it comes to relative newcomers in the Data Science field, there aren’t many out there doing better than Alyssa Columbus. Although she just graduated from college earlier this year, she already has a full-time data scientist role at Pacific Life, a laundry list of conference and symposium speaking engagements, and has founded a local […]

Linear Regression in Real Life

This post was written by Carolina Bento. She leads Data Analytics teams that empower companies to make data-driven decisions, and currently manages Product Analytics team at eero. This article was originally posted on Medium, and has been reposted with permission. We learn a lot of interesting and useful concepts in school but sometimes it’s not […]

Python vs R: Head to Head Data Analysis

Which is better for data analysis? There have been dozens of articles written comparing Python and R from a subjective standpoint. This article aims to look at the languages more objectively. We’ll analyze a data set side by side in Python and R, and show what code is needed in both languages to achieve the […]

How to Start Learning R for Data Science

In the world of data science, R is an increasingly popular programming language for a reason. It was built with statistical manipulation in mind, and there’s an incredible ecosystem of packages for R that let you do amazing things – particularly in data visualization – that would be much more difficult in Python. But R […]

11 Design Tips for Data Visualization

Here’s an important fact that’s easy to forget: our data is only as helpful as it is understandable. Most of the time, that means creating some kind of data visualization. And while a simple bar graph might cut it for internal work, making your data both visually understandable and visually attractive can help it get […]

How AI Will Change Healthcare

Editor’s note: This piece was written in collaboration with the MAA Center, an online resource for those who have been exposed to asbestos and those looking to learn more about it. Lauren Eaton is a Communications Specialist at MAA. We hope this piece will give you an idea of how data is becoming a part […]

Python Dictionary Tutorial

Python offers a variety of data structures to hold our information — the dictionary being one of the most useful. Python dictionaries quick, easy to use, and flexible. As a beginning programmer, you can use this Python tutorial to become familiar with dictionaries and their common uses so that you can start incorporating them immediately into […]

Understanding Regression Error Metrics

Human brains are built to recognize patterns in the world around us. For example, we observe that if we practice our programming everyday, our related skills grow. But how do we precisely describe this relationship to other people? How can we describe how strong this relationship is? Luckily, we can describe relationships between phenomena, such […]

Dataquest helped me get my dream job at Noodle.ai

Dataquest’s mission is to prepare real-world data scientists. Sunishchal Dev wanted to get a career in data science. He had a degree in Technology & Innovation Management and had business skills, but he needed to improve his technical skills and learn python to get the job he really wanted. Sunishchal had experience with online learning, […]

3 Mighty Good Reasons to Learn R for Data Science

Ahoy, mateys! Happy International Talk Like A Pirate Day! You may think a pirate’s life sounds like fun, but it isn’t all buried treasure and singing yo-ho-ho. Pirates have lots to do: Predicting profitability of plundering events based on crew size and ship features Optimizing trade routes to avoid the law, storms, and other pirates […]

Data Science Portfolio Project: Where to Advertise an E-learning Product

At Dataquest, we strongly advocate portfolio projects as a means of getting a first data science job. In this blog post, we’ll walk you through an example portfolio project. The project is part of our Statistics Intermediate: Averages and Variability course, and it assumes familiarity with: Sampling (populations, samples, sample representativity) Frequency distributions Box plots […]

Data Science Portfolio Project: Is Fandango Still Inflating Ratings?

At Dataquest, we strongly advocate portfolio projects as a means of getting your first data science job. In this blog post, we’ll walk you through an example portfolio project. The project is part of our Statistics Fundamentals course, and it assumes some familiarity with: Sampling (simple random sampling, populations, samples, parameters, statistics) Variables Frequency distributions […]

How to Overcome That Awkward Silence in Interviews

By Jillian Kramer We’ve all been there: what we thought was an excellent interview quickly degrades as we sit with the hiring manager in silence—left only to wonder what we have done wrong to encourage our colleague to stop speaking entirely. (Talk about awkward!) And so, we get it: “The silence in an interview is […]

Basic Statistics in Python: Probability

When studying statistics, you will inevitably have to learn about probability. It is easy lose yourself in the formulas and theory behind probability, but it has essential uses in both working and daily life. We’ve previously discussed some basic concepts in descriptive statistics; now we’ll explore how statistics relates to probability. Prerequisites: Similar to the […]

Preparing for the Data Science Job Hunt

Editor’s note: This piece was written in collaboration with SwitchUp, an online platform for researching and reviewing technology learning programs. Erica Freedman is a Content Specialist at SwitchUp. Job hunting is stressful, especially if you’re moving into an entirely new field. In this post, I give tips on finding data science jobs, looking up salaries, […]

A Data Science Project Style Guide

Employers usually give a lot of weight to a candidate’s portfolio when hiring for a junior data science role. Although you may be capable of technically impressive projects, your job hunt will suffer if you don’t pay enough attention to the stylistic aspects as well. A busy employer is not going to review poorly constructed […]

Basic Statistics in Python: Descriptive Statistics

The field of statistics is often misunderstood, but it plays an essential role in our everyday lives. Statistics, done correctly, allows us to extract knowledge from the vague, complex, and difficult real world. Wielded incorrectly, statistics can be used to harm and mislead. A clear understanding of statistics and the meanings of various statistical measures […]

DIY AI for the Future

Editor’s note: This post is the result of a collaboration with PredictX, a decision automation platform. Author Joni Lindes is a content writer at PredictX. AI is set to disrupt our current society on a major scale. According to Indeed, the number of roles in AI has risen by 485% in the UK since 2014, […]

Python Generators

Python generators are a powerful, but misunderstood tool. They’re often treated as too difficult a concept for beginning programmers to learn — creating the illusion that beginners should hold off on learning generators until they are ready. I think this assessment is unfair, and that you can use generators sooner than you think. In this […]

Take These 7 Small Steps To Make a Big Career Move

By Michele Lando One of the biggest fears many people face when it comes to career development is how to change or transition careers without getting pigeonholed into one industry or field. Believe it or not, changing careers isn’t as difficult as you may think. To make things a little less intimidating, here are 7 […]

Programming Best Practices For Data Science

The data science life cycle is generally comprised of the following components: data retrieval data cleaning data exploration and visualization statistical or predictive modeling While these components are helpful for understanding the different phases, they don’t help us think about our programming workflow. Often, the entire data science life cycle ends up as an arbitrary […]

How to Overcome Imposter Syndrome For Good

By Sarah Johnson I was working at a job I loved when I started to wonder whether I was a bit of a fraud. Digital strategy and client service was my forte. But when I was offered extra responsibilities that suddenly had me leading meetings with top affiliate global marketers (while I had minimal experience […]

Data Retrieval and Cleaning: Tracking Migratory Patterns

Advancing your skills is an important part of being a data scientist. When starting out, you mostly focus on learning a programming language, proper use of third party tools, displaying visualizations, and the theoretical understanding of statistical algorithms. The next step is to test your skills on more difficult data sets. Sometimes these data sets […]

Generating Climate Temperature Spirals in Python

Ed Hawkins, a climate scientist, tweeted the following animated visualization in 2017 and captivated the world: This visualization shows the deviations from the average temperature between 1850 and 1900. It was reshared millions of times over Twitter and Facebook and a version of it was even shown at the opening ceremony for the Rio Olympics. […]

Using Linear Regression for Predictive Modeling in R

Predictive models are extremely useful for forecasting future outcomes and estimating metrics that are impractical to measure. For example, data scientists could use predictive models to forecast crop yields based on rainfall and temperature, or to determine whether patients with certain traits are more likely to react badly to a new medication. Before we talk […]

Top 10 Machine Learning Algorithms for Beginners

Introduction The study of ML algorithms has gained immense traction post the Harvard Business Review article terming a ‘Data Scientist’ as the ‘Sexiest job of the 21st century’. So, for those starting out in the field of ML, we decided to do a reboot of our immensely popular Gold blog The 10 Algorithms Machine Learning […]

This Artist Turns the Forest Floor into Data Visualizations

Editor’s note: This post was written as part of a collaboration with iDataLabs, a marketing intelligence company. Author Julia Cook works in marketing at iDataLabs. We’re all familiar with data visualizations — word clouds, pie charts, pivot tables — but how does one put enquiries in paint? Patty Haller, a landscape artist from Seattle WA, may have figured that […]

Eric: “I wanted something practical”

Eric Sales De Andrade came to Dataquest via Quora. “I read a response from Vik and he seemed to know what he was writing about.” At the time, he worked in data mining— “But it was just putting stuff in a database. I wanted to get real with data.” He had originally tried DataCamp and a machine […]

Mike: “I wanted to grow my skills”

Mike Roberts didn’t plan on becoming a data scientist. After getting a degree in physics, he gave art management and professional poker playing a shot before becoming a BI analyst. He joined Dataquest to beef up those BI skills, but quickly learned he could switch to a much more interesting role within data science. For […]

Christian: “Consistency is Key”

After working in Business Intelligence, Christian L’Heureux took a break from data science. When he returned, as part of his MBA program, he found a changed world. He knew he needed to get up to speed quickly on the new landscape — especially Python. After trying DataCamp and CodeAcademy, he found Dataquest. “I liked the way […]

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