- Explain NLP Models with LIME, by Ayan Kundu - Jan 21, 2022.
It is important to know how LIME reaches to its final outputs for explaining a prediction done for text data. In this article, I have shared that concept by enlightening the components of LIME.
- The High Paying Side Hustles for Data Scientists, by Abid Ali Awan - Jan 20, 2022.
Learn about some unconventional ways to boost your income by freelancing, contracting, copywriting, career counseling, and consultancy.
- How to Process a DataFrame with Millions of Rows in Seconds, by Roman Orac - Jan 18, 2022.
TLDR; process it with a new Python Data Processing Engine in the Cloud.
- Data Science Web nugget Roundup, Jan 14: Kaggle Datasets & Python Debugging, by KDnuggets - Jan 15, 2022.
In our first weekly roundup of data science nuggets from around the web, check out a list of curated articles on Kaggle datasets, Python debugging tools, what it is data scientists do, an overview of YOLO, 2-dimensional PyTorch tensors, and the secrets of machine learning deployment.
- Running Redis on Google Colab, by Nava Levy - Jan 14, 2022.
Open source Redis is being increasingly used in Machine Learning, but running it on Colab is different compared to on your local machine or with Docker. Read on for a 2-step tutorial on how to do it.
- Transfer Learning for Image Recognition and Natural Language Processing, by Nisha Arya - Jan 14, 2022.
Read the second article in this series on Transfer Learning, and learn how to apply it to Image Recognition and Natural Language Processing.
- Top Five SQL Window Functions You Should Know For Data Science Interviews, by Terence Shin - Jan 13, 2022.
Focusing on the important concepts for data scientists.
- A (Much) Better Approach to Evaluate Your Machine Learning Model, by Olivier Blais - Jan 12, 2022.
Using one or two performance metrics seems sufficient to claim that your ML model is good — chances are that it’s not.
- Interpretable Neural Networks with PyTorch, by Dr. Robert Kübler - Jan 11, 2022.
Learn how to build feedforward neural networks that are interpretable by design using PyTorch.
- Fake It Till You Make It: Generating Realistic Synthetic Customer Datasets, by Matthew Mayo - Jan 11, 2022.
Finding the data you need is hard. So why not fake it?
- SQL Interview Questions for Experienced Professionals, by Nate Rosidi - Jan 7, 2022.
This article will show you what SQL concepts you should know as an experienced professional.
- What is Transfer Learning?, by Nisha Arya - Jan 5, 2022.
During transfer learning, the knowledge leveraged and rapid progress from a source task is used to improve the learning and development to a new target task. Read on for a deeper dive on the subject.
- Why Do Machine Learning Models Die In Silence?, by Thuwarakesh Murallie - Jan 5, 2022.
A critical problem for companies when integrating machine learning in their business processes is not knowing why they don't perform well after a while. The reason is called concept drift. Here's an informational guide to understanding the concept well.
- Learn Deep Learning by Building 15 Neural Network Projects in 2022, by Param Raval - Jan 4, 2022.
Here are 15 neural network projects you can take on in 2022 to build your skills, your know-how, and your portfolio.
- Hands-on Reinforcement Learning Course Part 3: SARSA, by Pau Labarta Bajo - Jan 3, 2022.
This is part 3 of my hands-on course on reinforcement learning, which takes you from zero to HERO . Today we will learn about SARSA, a powerful RL algorithm.