Explain NLP Models with LIME - 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 - 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 - 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 - 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 - 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 - 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 - Jan 13, 2022.
Focusing on the important concepts for data scientists.
A (Much) Better Approach to Evaluate Your Machine Learning Model - 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 - 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 - Jan 11, 2022.
Finding the data you need is hard. So why not fake it?
SQL Interview Questions for Experienced Professionals - Jan 7, 2022.
This article will show you what SQL concepts you should know as an experienced professional.
What is Transfer Learning? - 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? - 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 - 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 - 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.
- A Full End-to-End Deployment of a Machine Learning Algorithm into a Live Production Environment
3 Tools to Track and Visualize the Execution of Your Python Code
, by Khuyen Tran Avoid headaches when debugging in one line of code.
- Hands-On Reinforcement Learning Course, Part 2
- The Easiest Way to Make Beautiful Interactive Visualizations With Pandas
- Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model
- Versioning Machine Learning Experiments vs Tracking Them
- Tips & Tricks of Deploying Deep Learning Webapp on Heroku Cloud
- Alternative Feature Selection Methods in Machine Learning
- Cutting Down Implementation Time by Integrating Jupyter and KNIME
6 Predictive Models Every Beginner Data Scientist Should Master
, by Ivo Bernardo Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.
- Hands-On Reinforcement Learning Course, Part 1
- Federated Learning: Collaborative Machine Learning with a Tutorial on How to Get Started
Three R Libraries Every Data Scientist Should Know (Even if You Use Python)
, by Terence Shin Check out these powerful R libraries built by the world’s biggest tech companies.
- How to Get Into Data Analytics If You Don’t Have the Right Degree
- How to Speed Up XGBoost Model Training
- Cloud ML In Perspective: Surprises of 2021, Projections for 2022
Write Clean Python Code Using Pipes
, by Khuyen Tran A short and clean approach to processing iterables.
- Feature Selection: Where Science Meets Art
- Data Labeling for Machine Learning: Market Overview, Approaches, and Tools
- Introduction to Clustering in Python with PyCaret
- Inside DeepMind’s New Efforts to Use Deep Learning to Advance Mathematics
- Analyzing Scientific Articles with fine-tuned SciBERT NER Model and Neo4j
Building a solid data team
, by Romain Huet How do you put together a solid data science team when it comes to developing data-driven products? A variety of roles are available to consider, so which ones do you need and which are most crucial?
- Introduction to Binary Classification with PyCaret
- Using Datawig, an AWS Deep Learning Library for Missing Value Imputation
- What Does a Data Scientist Do?
- A Beginner’s Guide to End to End Machine Learning
- Meta-Learning for Keyphrase Extraction
How to Get Certified as a Data Scientist
, by Abid Ali Awan If you are early in your journey to becoming a Data Scientist, an interesting option is to earn certification by DataCamp, and this guide offers tips that will help beginners complete the challenges.
- Using PyCaret’s New Time Series Module
- Avoid These Mistakes with Time Series Forecasting
- 2021: A Year Full of Amazing AI papers — A Review
- How to Use Permutation Tests
5 Practical Data Science Projects That Will Help You Solve Real Business Problems for 2022
, by Terence Shin This curated list of data science projects offers real-life problems that will help you master skills to demonstration that you are technically sound and know how to conduct data science projects that add business value.
- Movie Recommendations with Spark Collaborative Filtering