Topic: Data Science
This page features most recent and most popular posts on Data Science.
Latest posts on Data Science
- Data Analysis Using Scala - Sep 24, 2021It is very important to choose the right tool for data analysis. On the Kaggle forums, where international Data Science competitions are held, people often ask which tool is better. R and Python are at the top of the list. In this article we will tell you about an alternative stack of data analysis technologies, based on Scala.
- How Data Scientists Can Compete in the Global Job Market - Sep 24, 2021Data scientists wanting to stay competitive or break into the field will need the right approach. These techniques will help them search for and secure a new position.
- Nine Tools I Wish I Mastered Before My PhD in Machine Learning - Sep 22, 2021Whether you are building a start up or making scientific breakthroughs these tools will bring your ML pipeline to the next level.
- Paradoxes in Data Science - Sep 17, 2021Have a look into some of the main paradoxes associate with Data Science and it’s statistical foundations.
- What 2 years of self-teaching data science taught me - Sep 17, 2021Many of us self-learn data science from the very beginning. While continuing to self-learn on demand is crucial, especially after you become a professional, there can be many pitfalls early on for learning the wrong way or missing out on key ideas that are important for the real-world application of data science.
Most popular (badge-winning) recent posts on Data Science
- 7 Differences Between a Data Analyst and a Data Scientist [Silver Blog]This article discusses the 7 key differences between data analysts and data scientists with an aim to help potential data analysts/scientists determine which is the right one for them. I touch on day-to-day tasks, skill requirements, typical career progression, and salary and career prospects for both.
- Data Science Cheat Sheet 2.0 [Silver Blog]Check out this helpful, 5-page data science cheat sheet to assist with your exam reviews, interview prep, and anything in-between.
- Learning Data Science and Machine Learning: First Steps After The Roadmap [Silver Blog]Just getting into learning data science may seem as daunting as (if not more than) trying to land your first job in the field. With so many options and resources online and in traditional academia to consider, these pre-requisites and pre-work are recommended before diving deep into data science and AI/ML.
- Most Common Data Science Interview Questions and Answers [Gold Blog]After analyzing 900+ data science interview questions from companies over the past few years, the most common data science interview question categories are reviewed in this guide, each explained with an example.
- GPU-Powered Data Science (NOT Deep Learning) with RAPIDS [Gold Blog]How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.
- A Brief Introduction to the Concept of Data [Silver Blog]Every aspiring data scientist must know the concept of data and the kind of analysis they can run. This article introduces the concept of data (quantitative and qualitative) and the types of analysis.
- Not Only for Deep Learning: How GPUs Accelerate Data Science & Data Analytics [Gold Blog]Modern AI/ML systems’ success has been critically dependent on their ability to process massive amounts of raw data in a parallel fashion using task-optimized hardware. Can we leverage the power of GPU and distributed computing for regular data processing jobs too?
- Why and how should you learn “Productive Data Science”? [Gold Blog]What is Productive Data Science and what are some of its components?
- Advice for Learning Data Science from Google’s Director of Research [Silver Blog]Surfing the professional career wave in data science is a hot prospect for many looking to get their start in the world. The digital revolution continues to create many exciting new opportunities. But, jumping in too fast without fully establishing your foundational skills can be detrimental to your success, as is suggested by this advice for data science newbies from Peter Norvig, the Director of Research at Google.
- 5 Lessons McKinsey Taught Me That Will Make You a Better Data Scientist [Gold Blog]How to stand out from your peers in the data world.
- Managing Your Reusable Python Code as a Data Scientist [Silver Blog]Here are a few approaches that I have settled on for managing my own reusable Python code as a data scientist, presented from most to least general code use, and aimed at beginners.
- What will the demand for Data Scientists be in 10 years? Will Data Scientists be extinct? [Gold Blog]Participate in the latest KDnuggets survey and share your opinion: what does the next decade have in store for data scientist demand?
- Data Scientists Will be Extinct in 10 Years [Platinum Blog]And why it’s not a bad thing.
- Top 10 Data Science Projects for Beginners [Gold Blog]Check out these projects for ideas to strengthen your skills and build a portfolio that stands out.
- Will There Be a Shortage of Data Science Jobs in the Next 5 Years? [Gold Blog]The data science workflow is getting automated day by day.
- How I Doubled My Income with Data Science and Machine Learning [Gold Blog]Many career opportunities exist in the ever-expanding domain of data. Finding your place -- and finding your salary -- is largely up to your dedication, focus, and drive to learn. If you are an aspiring Data Scientist or have already started your professional journey, there are multiple strategies for maximizing your earning potential.
- A checklist to track your Data Science progress [Silver Blog]Whether you are just starting out in data science or already a gainfully-employed professional, always learning more to advance through state-of-the-art techniques is part of the adventure. But, it can be challenging to track of your progress and keep an eye on what's next. Follow this checklist to help you scale your expertise from entry-level to advanced.
- Data Scientist, Data Engineer & Other Data Careers, Explained [Platinum Blog]In this article, we will have a look at five distinct data careers, and hopefully provide some advice on how to get one's feet wet in this convoluted field.
- Data Preparation in SQL, with Cheat Sheet! [Gold Blog]If your raw data is in a SQL-based data lake, why spend the time and money to export the data into a new platform for data prep?
- Rebuilding My 7 Python Projects [Silver Blog]This is how I rebuilt My Python Projects: Data Science, Web Development & Android Apps.