The 5 Most Important Principles of Data Visualization Shachee Swadia, Medium @ 2021-03-14 |
| |  | “Above all else, show the data.” — Edward Tufte |
17 types of similarity and dissimilarity measures used in data science. Mahmoud Harmouch, Towards Data Science - Medium @ 2021-03-13 |
| |  | The following article explains various methods for computing distances and showing their instances in our daily lives. Additionally, it will introduce you to the pydist2 package. Various ML metrics. “There is no Royal Road to Geometry.” — Euclid Quick note : Everything written and visualized has (...) |
5 Simple Ways to Tokenize Text in Python Frank Andrade, Towards Data Science - Medium @ 2021-03-13 |
| |  | Tokenizing text, a large corpus and sentences of different language. Tokenization is a common task a data scientist comes across when working with text data. It consists of splitting an entire text into small units, also known as tokens. Most Natural Language Processing (NLP) projects have (...) |
Getting Started with GitLab: The Absolute Beginner’s Guide Marie Lefevre, Towards Data Science - Medium @ 2021-03-13 |
| |  | How to use GitLab step by step, even if you have never heard of Git before Less than a year ago I had no idea what the word “Git” meant . To me, it was a rather barbaric term used by developer teams to talk to each other in a kind of coded language. Having a business background I thought I would (...) |
How to Boost Forecasting With Multiprocessing Justin Chae, Medium @ 2021-03-11 |
| |  | When and how to boost time series forecasting with ARIMA, Facebook Prophet, and PyTorch LSTM neural networks by pooling CPUs and computing… |
Using CycleGAN to perform style transfer on a webcam Ben Santos, Medium @ 2021-03-11 |
| | | As I have learned more about GANs, one particular application stands out to me: style transfer. The goal of style transfer is to learn how… |
The AI Index Report - Artificial Intelligence Index Stanford @ 2021-03-11 |
| | | The rise of AI inevitably raises the question of how much the technologies will impact businesses, labor, and the economy more generally. AI offers substantial benefits and opportunities for businesses, from increasing productivity gains with automation to tailoring products to consumers using (...) |
32 Advanced Techniques for Better Python Code Bruce H. Cottman, Ph.D., Medium @ 2021-03-11 |
| |  | Tips for Python documentation, coding, testing, verification, and continuous integration |
Step by Step process of Feature Engineering for Machine Learning Algorithms in Data Science elluru_pavan_kumar, Analytics Vidhya @ 2021-03-11 |
| |  | ArticleVideo Book Introduction Data Science is not a field where theoretical understanding helps you to start a carrier. It totally depends on the projects ... The post Step by Step process of Feature Engineering for Machine Learning Algorithms in Data Science appeared first on Analytics Vidhya . |
Analytical Hashing Techniques Scott Haines, Towards Data Science - Medium @ 2021-03-11 |
| |  | Spark SQL Functions to Simplify your Life Photo Credit: https://unsplash.com/@swimstaralex Anyone working in the field of analytics and machine learning will eventually need to generate strong composite grouping keys, and idempotent identifiers, for the data they are working with. These (...) |
35 Useful Docker commands Venkat Ranabothu, DevOps on Medium @ 2021-03-10 |
| | | I have tried to list down all the docker CLI commands used while playing with containers. Hope it helps! Continue reading on Medium » |
Teams support in Microsoft365R Revolutions @ 2021-03-10 |
| | | by Hong Ooi I’m happy to announce that version 2.0 of Microsoft365R, the R interface to Microsoft 365, is now on CRAN! This version adds support for Microsoft Teams, a much-requested feature. To access a team in Microsoft Teams, use the get_team() function and provide the team name or ID. You can (...) |
A function to speed up and simplify writing to SQL Server databases in R By Christoph, Hutsons-hacks @ 2021-03-10 |
| |  | I had a recent enquiry on our NHS-R community slack channel about which package is best to work with larger datasets, such as 5 million plus records, with high dimensionality. I got to thinking tha… |
Cheat Sheets R Views @ 2021-03-10 |
| |  | In a previous post , I described how I was captivated by the virtual landscape imagined by the RStudio education team while looking for resources on the RStudio website. In this post, I’ll take a look at Cheatsheets another amazing resource hiding in plain sight. Apparently, some time ago when I (...) |
7 Must-Know Ideas about NoSQL Skye Tran, Towards Data Science - Medium @ 2021-03-09 |
| |  | 7 Must-Know Ideas about NoSQL to Avoid Decisions You’ll Regret How to avoid those dreaded pitfalls and “gotcha” moments when selecting databases for your next application? Asking any developer of an enterprise application, and you’ll know how much they are feeling frustrated with the limitations of (...) |
How to parallelize for loops in Python and Work with Shared Dictionaries Rahul Banerjee, Towards Data Science - Medium @ 2021-03-09 |
| |  | This article will cover the implementation of a for loop with multiprocessing and a for loop with multithreading. We will also make multiple requests and compare the speed. Table of Contents Sequential MultiProcessing MultiThreading Sharing Dictionary using Manager ‘Sharing’ Dictionary by combining (...) |
Streamlit Guide: How to Build Machine Learning Applications Derrick Mwiti, neptune.ai @ 2021-03-09 |
| |  | Building machine learning applications keeps getting easier. With Streamlit, you can develop machine learning apps quickly and easily. You can also use the Streamlit sharing platform to deploy your applications in just a couple of clicks. It doesn’t take long to start developing with Streamlit, (...) |
Stop One-Hot Encoding your Categorical Features — Avoid Curse of Dimensionality Satyam Kumar, Medium @ 2021-03-09 |
| |  | Techniques to Encode Categorical Features with many Levels/Categories |
Jupyter Notebook & Spark on Kubernetes Itay Bittan, Towards Data Science - Medium @ 2021-03-09 |
| |  | The complete guide for setting up your local environment Jupyter notebook is a well-known web tool for running live code. Apache Spark is a popular engine for data processing and Spark on Kubernetes is finally GA ! In this tutorial, we will bring up a Jupyter notebook in Kubernetes and run a Spark (...) |
Python Argparse: Parser for command-line options, arguments and sub-commands Knoldus Inc., DevOps on Medium @ 2021-03-08 |
| |  | Continue reading on Medium » |
A Comprehensive Introduction to Bayesian Deep Learning Joris Baan, Towards Data Science - Medium @ 2021-03-04 |
| |  | Bridging the Gap Between Basics and Modern Research. Table of Contents 1. Preamble 2. Neural Network Generalization 3. Back to Basics: The Bayesian Approach 3.1 Frequentists 3.2 Bayesianists 3.3 Bayesian Inference and Marginalization 4. How to Use a Posterior in Practice? 4.1 Maximum A Posteriori (...) |
