Rahul Agarwal

Rahul Agarwal is a Machine Learning Engineer at Facebook. Previously, he was a data scientist at Walmart Labs India, and worked at several startups. Find him at @MLWhiz on Twitter, or mlwhiz.com

The 5 Classification Evaluation Metrics Every Data Scientist Must Know

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on October 16, 2019 in Data Scientist, Machine Learning, Metrics, Python
This post is about various evaluation metrics and how and when to use them.
6 bits of advice for Data Scientists

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on September 25, 2019 in Advice, Data Cleaning, Data Scientist, Metrics, Overfitting, Statistics
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

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on September 20, 2019 in Automated Machine Learning, Hyperparameter, Machine Learning, Modeling
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

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on September 18, 2019 in Algorithms, Sampling
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.
The 5 Graph Algorithms That Data Scientists Should Know

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on September 10, 2019 in Algorithms, Data Science, Data Scientist, Graph, Python
In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.
The Hitchhiker’s Guide to Feature Extraction

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on June 3, 2019 in Feature Engineering, Feature Extraction, Feature Selection, Kaggle, Python
Check out this collection of tricks and code for Kaggle and everyday work.
What my first Silver Medal taught me about Text Classification and Kaggle in general?

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on May 13, 2019 in Advice, Competition, Cross-validation, Kaggle, Python, Text Classification
A first-hand account of ideas tried by a competitor at the recent kaggle competition 'Quora Insincere questions classification', with a brief summary of some of the other winning solutions.
Good Feature Building Techniques and Tricks for Kaggle

By Rahul Agarwal, MLE @ FB | Ex-Walmart DS | MLWhiz on December 31, 2018 in Feature Engineering, Kaggle, Tips
A selection of top tips to obtain great results on Kaggle leaderboards, including useful code examples showing how best to use Latitude and Longitude features.

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