About Rahul Agarwal

Rahul Agarwal is a data scientist consultant and big data engineer working with WalmartLabs. Previously, Rahul worked at startups like Fractal and MyCityWay and coglomerates like Citi. Find him at @MLWhiz on Twitter, or mlwhiz.com

Rahul Agarwal Posts (14)

• Five Cognitive Biases In Data Science (And how to avoid them) - 12 Jun 2020
  
  Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work. Learn more about five biases that can all too easily make your seemingly objective work become surprisingly subjective.
• Don’t Democratize Data Science - 02 Jun 2020
  
  A plethora of online courses and tools promise to democratize the field, but just learning a few basic skills does not a true data scientist make.
• The 5 Most Useful Techniques to Handle Imbalanced Datasets - 22 Jan 2020
  
  This post is about explaining the various techniques you can use to handle imbalanced datasets.
• Handling Trees in Data Science Algorithmic Interview - 16 Jan 2020
  
  This post is about fast-tracking the study and explanation of tree concepts for the data scientists so that you breeze through the next time you get asked these in an interview.
• Learning SQL the Hard Way - 08 Jan 2020
  
  Simply put: This post is about installing SQL, explaining SQL and running SQL.
• How to Write Web Apps Using Simple Python for Data Scientists - 22 Oct 2019
  
  Convert your Data Science Projects into cool apps easily without knowing any web frameworks.
• The 5 Classification Evaluation Metrics Every Data Scientist Must Know - 16 Oct 2019
  
  This post is about various evaluation metrics and how and when to use them.
• 6 bits of advice for Data Scientists - 25 Sep 2019
  
  As a data scientist, you can get lost in your daily dives into the data. Consider this advice to be certain to follow in your work for being diligent and more impactful for your organization.
• Automate Hyperparameter Tuning for Your Models - 20 Sep 2019
  
  When we create our machine learning models, a common task that falls on us is how to tune them. So that brings us to the quintessential question: Can we automate this process?
• The 5 Sampling Algorithms every Data Scientist need to know - 18 Sep 2019
  
  Algorithms are at the core of data science and sampling is a critical technical that can make or break a project. Learn more about the most common sampling techniques used, so you can select the best approach while working with your data.