Python Style Guide | How to Write Neat and Impressive Python Code
Overview The Python Style Guide will enable you to write neat and beautiful Python code Learn the different Python conventions and other nuances of …
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7 Open Source Data Science Projects you Should Add to your Resume
Overview Open source data science projects add a lot of value to your resume and help you stand out in an interview Here are …
4 Simple Ways to Split a Decision Tree in Machine Learning
Overview How do you split a decision tree? What are the different splitting criteria when working with decision trees? Learn all about decision tree …
Hugging Face Releases New NLP ‘Tokenizers’ Library Version (v0.8.0)
Hugging Face is at the forefront of a lot of updates in the NLP space. They have released one groundbreaking NLP library after another …
22 Widely Used Data Science and Machine Learning Tools in 2020
Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20 …
3 Building Blocks of Machine Learning you Should Know as a Data Scientist
Overview A machine learning system consists of multiple building blocks that need to be managed Learn about the three key building blocks of machine …
10 Compelling Reasons you Should Use JupyterLab for Data Science Coding
Overview JupyterLab is a brilliant coding environment to perform data science tasks These 10 reasons will convince to switch to JupyterLab from Jupyter Notebooks …
New to Kaggle? Here’s How you can Get Started with Kaggle Competitions
Overview Kaggle can often be intimating for beginners so here’s a guide to help you started with data science competitions We’ll use the House …
Statistics for Analytics and Data Science: Hypothesis Testing and Z-Test vs. T-Test
Overview Hypothesis testing is a key concept in statistics, analytics, and data science Learn how hypothesis testing works, the difference between Z-test and t-test, …
AUC-ROC Curve in Machine Learning Clearly Explained
AUC-ROC Curve – The Star Performer! You’ve built your machine learning model – so what’s next? You need to evaluate it and validate how …
