Functions that saved me a lot of time and frustration
No title available
$LAYYYTER
Stranger Things
will byers stan first human second
Claire Keane
noise dept.
Monterey Bay Aquarium
Misplaced Lens Cap

@theartofmadeline
Xuebing Du

if i look back, i am lost
I'd rather be in outer space 🛸
cherry valley forever
YOU ARE THE REASON

祝日 / Permanent Vacation
No title available
"I'm Dorothy Gale from Kansas"

Kiana Khansmith

PR's Tumblrdome
Sade Olutola

seen from United States
seen from Qatar
seen from United States
seen from Indonesia
seen from United States

seen from United States

seen from Singapore
seen from United States

seen from United States
seen from United Kingdom
seen from United States
seen from Denmark

seen from United States

seen from United States
seen from South Africa

seen from Germany
seen from United States

seen from Norway

seen from Canada

seen from United States
@datasciencethings
Functions that saved me a lot of time and frustration
Every once in a while, there comes a library or framework that reshapes and reimagines how we look at the field of deep learning. The…
The ‘optimal’ solution to Dunder Data Challenge #3 will be presented. It does not use apply and shows a 20x speedup over the naive…
Short Python snippets that you can quickly learn and use in your work or personal needs
Creating a production-ready API with FastAPI + Uvicorn
An Overview Of Great Features In Pandas 0.25 Python Library
4 libraries for better visualisation, explanation and interpretation of models
Stop using StandardScaler from Sklearn as a default feature scaling method can get you a boost of 7% in accuracy!
For a recent data science project, I developed a supervised learning model to classify the booking location of a first-time user of the…
“Let’s Talk About Machine Learning Ensemble Learning In Python” by Farhad Malik https://link.medium.com/E9AIikKjrY
Overview Complete guide on natural language processing (NLP) in Python Learn various techniques for implementing NLP including parsing & text processing Understand how to use NLP for text feature engineering Introduction According to industry estimates, only 21% of the available data is present in structured form. Data is being generated
Learn about some of the most useful BASH commands and the utility they offer.
The NumPy package is the workhorse of data analysis, machine learning, and scientific computing in the python ecosystem. It vastly simplifies manipulating and crunching vectors and matrices. Some of python’s leading package rely on NumPy as a fundamental piece of their infrastructure (examples include scikit-learn, SciPy, pandas, and tensorflow). Beyond the ability to slice and dice numeric data, mastering numpy will give you an edge when dealing and debugging with advanced usecases in these libraries. In this post, we’ll look at some of the main ways to use NumPy and how it can represent different types of data (tables, images, text…etc) before we an serve them to machine learning models.
Coming across an ImportError similar to the one in the image below can be annoying.
121 resources to help you land your data science dream job
Jupyter Notebook is a powerful tool for data analysis. Here are 28 tips, tricks, and shortcuts to turn you into a Jupyter notebooks power user!
The pandas library is the most popular data manipulation library for python. It provides an easy way to manipulate data through its…