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“Any woman who chooses to behave like a full human being should be warned that the armies of the status quo will treat her as something of a dirty joke. That’s their natural and first weapon.” ~Gloria Steinem
Alongside much of the turmoil and debate many of us are currently experiencing, one persistent target I have n... | ['Icantbreathe', 'Rape Culture', 'Abortion', 'Feminism'] |
I Think I’m Finally Clean: Taylor Swift, Sexual Assault, and Coming Forward
I think when I first came to understand sexual assault and harassment, I was 11 or 12. My family and I were walking in Chicago together. We had just gotten up to enjoy time around the city, and were currently heading to Breakfast to enjoy a go... | ['Harassment', 'Rape Culture', 'Taylor Swift', 'Feminism', 'Sexual Assault'] |
Covid-19 Efforts
We’re always working to support, amplify, and further the work of our partner departments, and that was no different as the pandemic unfolded in Boston. In the early days, we aimed to be extra pairs of hands and ears to our colleagues who were responding directly to the crisis from the front lines.
W... | ['Civic Technology', 'Local Government', 'Civic Innovation', 'Civic Engagement', 'Civic Design'] |
Amid the reopening of the city and the $1 billion-plus in homelessness spending, we learned that Sup. Aaron Peskin, the lion of San Francisco’s progressive movement, not only would seek treatment for alcohol abuse but also that he was apologizing for “the tenor” of his discourse. His long-noted nastiness, bullying, and... | ['San Francisco', 'Culture', 'Communication', 'Civic Engagement', 'Politics'] |
Below is Superintendent Chris Reykdal’s statement on yesterday’s events in Olympia and in Washington D.C.
Editor’s Note: This story was originally published in Chris Reykdal’s Medium publication, which was sunset in May 2021. Statements from Superintendent Reykdal will continue to appear in the main OSPI feed.
Superi... | ['Government', 'Civic Engagement', 'Education', 'K 12 Education', 'Civics'] |
As technology advances, these harmful power imbalances risk being replicated further and faster. The incentives, values and ownership models baked into finance will play crucial roles in the means of creation and distribution: how behavioural data from mobile phones, public spaces and smart homes are owned and used; or... | ['Design Thinking', 'Civic Engagement', 'Climate Change', 'Community', 'Systems Thinking'] |
John Snow’s Cholera Map of 1854. If you think about it, it’s actually an amazing example of early civic design. More from The Guardian.
TLDR version: We’re launching a new community and conference on civic design; sign up here for details/announcements.
Talk talk talk
Over the last couple of months, I’ve been on a l... | ['Citizen Engagement', 'Civic Innovation', 'Civic Engagement', 'User Experience', 'Civic Design'] |
Our progress on ethics, fairness, and transparency in assessments — and a look ahead at 2021 Cook County Assessor Mar 3·18 min read
On March 2nd, 2021, Assessor Fritz Kaegi spoke to the City Club of Chicago about the operations of the Cook County Assessor’s Office and offered a preview at the priorities for the year a... | ['War Games', 'Property Taxes', 'Civic Engagement', 'Govtech', 'The Fugitive'] |
Well, we did it.
Manny’s has survived the pandemic with the help of our community, the federal, state, and San Francisco government, our incredible staff, hard constant marathon-like work, and a healthy dash of good luck.
July 4th will be our grand re-opening party.
Register for it here!!
I am sitting here on the l... | ['Small Business', 'San Francisco', 'Democratic Party', 'Civic Engagement', 'Politics'] |
TL;DR
My90 launched in response to crises between communities and police. Five years later, we are joining Axon to scale our work. Read our personal story of founding My90 and why we believe in Axon’s potential to shape the future of public safety.
Mustafa: My first memory of police is being falsely accused of shopli... | ['Civic Engagement', 'Community', 'Police', 'Startup', 'Public Safety'] |
Thanks Tom, your useful exercise takes the “dosage” metaphor to a logical next step. This framework both spotlights the puzzling, persistent practice of expecting just a few meetings to change the world — and reveals the term’s limitations.
My original intent with using that medicalized imagery was to communicate why ... | ['Accountability', 'Civic Engagement', 'Governance', 'Participation'] |
Our all-hands meeting this morning
Over the last year we’ve announced our first grants, started working closely with our grantees — and just last week introduced our first CEO, Sarabeth Berman, who is stepping into the big shoes that John Thornton created as our day-to-day leader for the last 14 months.
What’s exciti... | ['Civic Engagement', 'Local News', 'Democracy', 'Nonprofit News', 'Philanthropy'] |
Civic engagement is more popular than ever as people across all ideologies push for change. Anyone who cares about civic matters needs to take action to advocate for the causes they believe in. These five activities should be on anyone’s list.
Stay Informed
The first and most important step to civic engagement is to ... | ['Rajkumar Surisetti', 'Civic Engagement', 'Philanthropy'] |
If there is any way that we can fight for justice against racism, I learned from my experience with KAGC that it begins with raising our own voices and standing up for ourselves.
When I arrived in Washington, D.C. for the 2020 KAGC U Leadership Summit, my fellow executive officer at KASA and I had no expectations of h... | ['Civic Engagement', 'Advocacy', 'Identity', 'Grassroots', 'Korean American'] |
Andre Lefebvre said
…we have been sleeping at the wheel, making decisions based on ideas of prosperity rather than values of humanity.
As Americans, our big idea of prosperity has been the Grandiose American Dream: everyone can prosper if they look out for themselves; if they don’t, it’s their problem.
I picture Cov... | ['Covid 19', 'Civic Engagement', 'Social Justice', 'Humanitarian', 'Covert 1dollar'] |
As new cases of COVID-19 continue to develop across North America, citizens are receiving communication from their city and taking action through SeeClickFix. Correspondence through SeeClickFix keeps citizens up-to-date as new information arises. Given the uncertainty we all feel, community leaders are taking steps in ... | ['Civictech', 'Covid 19', 'Seeclickfix', 'Civic Engagement', 'Community'] |
On February 19, 2020, Knight Foundation released a new study that sheds light on the 100 million Americans who don’t vote, their political views and what they think about the 2020 election. Knight’s Evette Alexander shares more below. View the report website, the full report and the full press release for more informat... | ['Voting', 'Civic Engagement', '2020 Presidential Race', 'Politics', 'Democracy'] |
In this instalment of Mentor Mondays we catch up with Ashish VR to find out how this Engineering graduate wound up mentoring young public problem solvers with Reap Benefit.
Ashish VR handing over a Skill Certificate to a Solve Ninja.
An early habit of taking on responsibility
Ashish is always volunteering to help ou... | ['Environmental Issues', 'Civic Engagement', 'Public Problem Solving', 'Mentor Mondays', 'Mentoring'] |
Speed bump made of clay
In popular jargon in Burkina Faso, they are called in french “gendarmes couchés” which literal translation is ‘lying police officers’. These are speed bumps, these bumps on the road to force users, especially motorists to slow down. They make it possible to limit accidents and save human lives ... | ['Burkina Faso', 'Civic Engagement', 'Road Safety', 'Infrastructure'] |
youth participation
In every sector and every space today, young people are on the agenda. It is therefore ironical that despite all the attention, we continue to be grossly underrepresented and misrepresented.
Only 6.5% of the country’s parliament is made up of youth. Not only that, programs and schemes that are mea... | ['Civic Engagement', 'Governance', 'Youth'] |
Nirmala Naik’s first job after her Masters programme was with Reap Benefit, and it started right in the middle of the pandemic lockdown. But Nirmala didn’t let that stand in her way of enthusiastically becoming a key member of our team in Nelamangala District. Recently she started working with Government Schools and Af... | ['Civic Engagement', 'Mentoring', 'Organization Culture', 'Non Profit Organization', 'Solve Ninjas'] |
What journalists can do year-round to earn trust with their political reporting Lynn Walsh Follow Apr 7 · 5 min read
Image Credit: Akshay Gupta
Journalists had a lot to deal with when covering the 2020 election.
They were accused of having a liberal bias, and of covering conservative and progressive ideas and candid... | ['Government', 'Civic Engagement', 'News', 'Politics', 'Democracy'] |
LEAD Mongolia Fellow Soronzonbold Alexandr
By Meghan Burland, Chief of Party, Leaders Advancing Democracy (LEAD) Mongolia
In many places, local elected officials are often the people taking care of a citizen’s daily needs — from determining local community development projects to maintaining roads and infrastructure.... | ['Youth', 'Elections', 'Local Government', 'Civic Engagement', 'Mongolia'] |
Image Credits: Tom de Boor, Shutterstock, et al
2021 began with a wave of material and dialogue on the importance of constructive civic learning and engagement to the future of our American democracy. The question is whether this wave will sweep across the country in the years to come, substantially strengthening our ... | ['Civic Engagement', 'Education', 'Civics', 'Democracy', 'Education Reform'] |
Syeda, in conversation with Nadeem Uncle. This Q&A has been edited for grammar and clarity. Photographs are from Nadeem’s personal collection.
Where is home for you? Do you feel like we’re part of a similar community and where does our connection stem from?
Home is Duluth, Georgia. When I came to this country, I was ... | ['Civic Engagement', 'Asian American', 'Georgia', 'Mentorship'] |
A More United Politics
Politics Isn’t All Bad and Your Kids Should Know It
As a part of an interdisciplinary series looking to restore a sense of unity in the U.S. after a fractious election period I was asked to give a set of answers to the prompt, What are 5 Steps That Each Of Us Can Take To Proactively Help Heal O... | ['Polarization', 'Parenting', 'Civic Engagement', 'Civil Discourse', 'Politics'] |
Over the past decade, I have worked on more political and issue campaigns than I can count. The first time I was eligible to vote in a general election, I cast my ballot to elect Barack Obama and I have been campaigning for social and economic justice ever since. The hope and inspiration I felt back then is alive today... | ['Elections', 'Social Change', 'Activism', 'Civic Engagement', 'Politics'] |
Retrieved via creative commons search
Earlier this year, PACE stepped further into our identity as a philanthropic laboratory by sharing the specifics of where we will focus our energy in the months ahead. In the ways we serve our members and the areas we make learning and experimentation participatory and actionable,... | ['Philanthropy', 'Civic Engagement', 'Racial Equity', 'Democracy', 'Pace Updates'] |
Written by Dr. Lacretia Carroll, Training Director, Leaders of Color Memphis
Leaders of Color fellows study principles and applications of civic engagement in our proprietary curriculum
Spoiler Alert: The answer to this question is a resounding “yes, and we’re doing it every day.”
Academically, civic engagement is d... | ['Civic Engagement', 'Community Organizing'] |
Being the lead product manager for a civic engagement platform Participate Melbourne*, I am a big advocate for how technology better facilitates the shaping of cities. So, I was thrilled to be given the opportunity to lead a piece of research last year on ‘Demystifing Planning’, with particular focus on planning scheme... | ['Human Centered Design', 'City Planning', 'Civic Engagement', 'Civic Innovation'] |
In less than 24 hours, on September 14, 2021, Californians will decide the future of our state.
Californians will vote on whether or not to recall Governor Gavin Newsom. The Governor has a lot of power to influence the direction of California. They can fight for or roll back progress through policies, the state budget... | ['Polling Places', 'California', 'Civic Engagement', 'Recall Elections', 'Oakland'] |
Compared to the city as a whole, North Minneapolis is more racially diverse, has more young people, and — at an estimated $40,000 — has a lower average household income. It’s a proud community, with many assets made up of people, places and a culture that have been impacted by present and historic inequities, includi... | ['Cities', 'Sustainability', 'Civic Engagement', 'Resilience', 'Community'] |
For example, if a decentralized organization such as the DAO adopts pain tokens, we can consider the following changes in the automated organizational structure without the intervention of human will (politics).
N: A completely flat and decentralized network-like organization, tentatively assumed.
T=N(T): tree-like r... | ['Civictech', 'Supply Chain', 'Civic Engagement', 'Blockchain', 'Playstation 3'] |
Tabular data is the most common type of data that Data Science practitioners work with. In this format, data is arranged in the form of rows and columns.
Let’s see some common problems faced with tabular data and how to solve them.
🔢 Handling Numerical Data
Let's create a synthetic dataset using the sklearn.dataset... | ['Data Science', 'Machine Learning', 'Feature Engineering'] |
Why feature engineering?
In reality, feature engineering becomes vital when you start transitioning into Big Data. Big Data analytics is and will always remain in high demand because, as of now, there is almost no way you can learn how to work on a gigantic dataset on your own. The only way to start approaching big da... | ['Encoding', 'Feature Engineering', 'Feature Extraction', 'Embedding', 'Feature Selection'] |
Photo by Dominik Scythe on Unsplash
Content
Introduction What is Feature Selection What Makes Some Feature Better Than Others Feature Selection by Label Information Supervised Feature Selection Unsupervised Feature Selection Feature Selection — Data Perspective Characteristics of Feature Selection Algorithm Feature S... | ['Feature Engineering', 'Feature Selection', 'Dimensionality Reduction', 'Data Science', 'Machine Learning'] |
Building Real-Time ML Pipelines with a Feature Store
Transition from batch to real time with an integrated feature store Adi Hirschtein Follow Jan 13 · 9 min read
The Next Stage of Feature Stores
The buzz around feature stores has increased in machine learning circles in the last few months, and the topic indeed des... | ['Feature Engineering', 'Feature Store', 'Data Science', 'Machine Learning', 'Mlops'] |
Feature Engineering on Time-Series Data for Human Activity Recognition
Transforming raw signal data of smartphone accelerometer and creating new features from it for identifying six common human activities. Pratik Nabriya Jun 29·12 min read
Photo by Jan Huber on Unsplash
Objective
While exploring the area of human ... | ['Feature Engineering', 'Data Science', 'Time Series Analysis', 'Deep Dives', 'Machine Learning'] |
Wouldn’t it be nice if you could quickly create features using arbitrary Python code? That is when Patsy comes in handy.
What is Patsy?
Patsy is a Python library that allows data transformation using arbitrary Python code.
With Patsy, you could use human-readable syntax such as life_expectancy ~ income_group + year ... | ['Feature Engineering', 'Editors Pick', 'Data Science', 'Data Visualization', 'Machine Learning'] |
A Swiss Knife python package for fast Data Science arita37 May 15·4 min read
Have you ever dreamed of having some snippets of code to read any type of files on disk, display many graphs at same time, create and auto-size save histogram in one liner in python,…. ?
Of course, there are pandas, matplotlib, seaborn, but ... | ['Feature Engineering', 'Python', 'Data Science', 'Data Visualization', 'Machine Learning'] |
Observations based on the above plots:
Males and females are almost equal in number and on average median charges of males and females are also the same, but males have a higher range of charges. Insurance charges are relatively higher for smokers. Charges are highest for people with 2–3 children Customers are almost ... | ['Gridsearchcv', 'Feature Engineering', 'Accuracy', 'Feature Transformation', 'Regression'] |
Some of you may not be that familiar with the concept of an ‘enterprise feature store’ in the world of data science, but I am pretty sure you have either interacted with or may have designed a feature store to solve some of the requirements for your project.
Let’s take an example. One of the most common use cases in m... | ['Feature Engineering', 'Tecton', 'Feature Store', 'Artificial Intelligence', 'Machine Learning'] |
Feature Engineering and Integration of COVID-19 Panel Data
As COVID-19 sweeps through the globe, we watch intently the climbing number of new cases and its impact on individuals, families, and countries. There is a tremendous influx of information on COVID-19 and significant analytics efforts in understanding these da... | ['Feature Engineering', 'United States', 'Statistics', 'Socialdistancing', 'Covid 19'] |
Machine Learning with Datetime Feature Engineering: Predicting Healthcare Appointment No-Shows
Dates and times are rich sources of information that can be used with machine learning models. However, these datetime variables do require some feature engineering to turn them into numerical data. In this post, I will demo... | ['Data Science', 'Machine Learning', 'Feature Engineering', 'Healthcare'] |
Transform Reality with Pandas
Photo by Nick Wood on Unsplash
Pandas makes python easy
Pure python is a beautifully clear language. But pandas really dumbs it down. Simplifying the python scripting language makes it easier to do even more complex feats of programming. DataFrame operations make math, science, explorat... | ['Feature Engineering', 'Data Engineering', 'Python', 'Data Science', 'Pandas'] |
You read the title and you might wonder why someone would want to automatically detect if a given feature is either numerical or categorical. This will come in handy for a greater task because it is just a step to handle missing values in a dataset(for a general machine learning problem). The end goal is to be able to ... | ['Feature Engineering', 'Python', 'Data Science', 'Logistic Regression', 'Features'] |
A categorical variable is one that has two or more categories (values). There are two types of categorical variable, nominal and ordinal. A nominal variable has no intrinsic ordering to its categories. For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to th... | ['Data Science', 'Feature Engineering', 'Python3', 'Categorical Variable'] |
Data Science Buzzwords: Feature Engineering
Feature Engineering is one of those terms that, on the surface, seems to mean exactly what it is saying: you want to refactor or create something from the data that you have.
Okay, fine…but what does that actually mean in real life when you’re sitting in front of your data ... | ['Feature Engineering', 'Programming', 'Data Science', 'Artificial Intelligence', 'Machine Learning'] |
But to our rescue comes some of the cool tools which automates the whole feature engineering process and creates a large pool of features in a very short span for both classification and regression tasks.
We have found following tools which automates the whole feature engineering process and creates large number of fe... | ['Feature Engineering', 'Meta Learning', 'Machine Learning', 'Automl', 'Features'] |
Why Feature Engineering?
At the start of every machine learning project, raw data will inevitably be messy and unsuitable for training a model. The first step is always data exploration and cleaning, which involves changing data types and removing or imputing missing values.
With a certain understanding of the data a... | ['Feature Engineering', 'Python', 'Data Science', 'Artificial Intelligence', 'Machine Learning'] |
Enhancing categorical features with Entity Embeddings
Let’s pretend you are the owner of a pub, and you want to predict how many beers your establishment is going to sell on a given day based on two variables: the day of the week and the current weather. We can in some ways imagine that weekends and warmer days are go... | ['Data Science', 'Machine Learning', 'Feature Engineering', 'Data Engineering'] |
Extracting the patterns using TA-Lib
With TA-Lib, extracting patterns is super simple. We can start by installing the module from https://github.com/mrjbq7/ta-lib. The repository contains easy to follow instructions for the installation process.
After the installation, we start by importing the module:
import talib
... | ['Feature Engineering', 'How To', 'Python', 'Algorithmic Trading', 'Candlestick Patterns'] |
In machine learning, we often encounter geographical or geospatial data such as latitude and longitude to be used as features. Some other geospatial data may include city, area code and other objects which may enrich latent relationships between the variables.
In this tutorial, it is assumed that the latitude and long... | ['Feature Engineering', 'Machine Learning', 'Regression Modeling', 'Geospatial Features', 'Geospatial Data'] |
Feature engineering is the process of transforming your input data in such a way that it will be more representative of the Machine Learning Algorithms. However, it is very often forgotten because of the inexistence of an easy-to-use package. That’s why we decided to create the one — imperio, the third our unforgivable... | ['Feature Engineering', 'Data', 'Data Science', 'Artificial Intelligence', 'Machine Learning'] |
Feature engineering is the process of transforming your input data in such a way that it will be more representative of the Machine Learning Algorithms. However, it is very often forgotten because of the inexistence of an easy-to-use package. That’s why we decided to create the one — imperio, the third our unforgivable... | ['Feature Engineering', 'Data', 'Data Science', 'Artificial Intelligence', 'Machine Learning'] |
Feature Reduction Using PCA
PCA is a dimension reduction method that takes datasets with a large number of features and reduces them to a few underlying features. PCA finds the underlying features in a given dataset by performing the following steps:
1. Calculate the covariance of the matrix of features
2. Calculate... | ['Feature Engineering', 'Classification', 'Feature Reduction', 'Data Science', 'Machine Learning'] |
Feature selection is a crucial part of any machine learning project, the wrong choice of features to be used by the model can lead to worse results, as such many techniques and methods were elaborated to get the optimal set of features.
In the case of supervised learning, this task is relatively easy thanks to preexis... | ['Feature Engineering', 'Unsupervised Learning', 'Clustering', 'Data Science', 'Machine Learning'] |
The Machine Learning Lifecycle and MLOps: Building and Operationalizing ML Models — Part I Kevin Petrie Follow Jul 1 · 7 min read
Source: Eckerson.com
This article was originally published at eckerson.com
Machine learning was supposed to make things easy by computerizing human cognition. But it made life harder than... | ['Feature Engineering', 'Ml Model', 'Ml Model Deployment', 'Machine Learning', 'Mlops'] |
Photo by Taras Shypka on Unsplash
It has been a great year for NVIDIA on RecSys competitions, having won four contests in the last 12 months — ACM RecSys Challenge 2020 and 2021 (both organized by Twitter), WSDM 2021 WebTour Workshop Challenge 2021 (organized by Booking.com) and now the SIGIR 2021 Workshop on E-commer... | ['Feature Engineering', 'Recommender Systems', 'Neural Networks', 'Rapids Ai', 'Nvidia'] |
How to do feature engineering?
Let’s see different strategies of feature engineering. In this article, we won’t see all the methods, but the most popular ones.
Adding and dropping features:
Let’s assume we do have the following features:
Price of houses
If we want to predict the price of a flat, the number of plan... | ['Feature Engineering', 'Data Science', 'Artificial Intelligence', 'Algorithms', 'Machine Learning'] |
Model Robustness
We would all like our Machine Learning models generalize on the unseen data, but often find that our model performance drops when the new data do not look like the old data, that is have a different distribution. For example, a medical diagnostics system we trained on the data from one country does no... | ['Causality', 'Feature Engineering', 'Feature Selection', 'Causal Inference', 'Machine Learning'] |
About a year ago I was working on a regression model, which had over a million features. Needless to say, the training was super slow, and the model was overfitting a lot. After investigating this issue, I realized that most of the features were created using 1-hot encoding of the categorical features, and some of them... | ['Kernel Trick', 'Feature Engineering', 'Graph Theory', 'Data Science', 'Machine Learning'] |
AsynDGAN structure. It is a Single-Generator Multi-Discrminator GAN structure
Generative Adversarial Networks (GANs) are an emerging methodology to synthesize data, ranging from images, to text, and to tables. The key components of GANs are training two competing neural networks, i.e., generator and discriminator, whe... | ['Feature Engineering', 'Distributed Systems', 'Gan', 'Tabular Data'] |
Almost all machine learning models will suffer from the curse of dimensionality, so today's post is dedicated to the technique of dimensionality reduction.
We will go over what exactly the curse of dimensionality is and how it affects the performance of your models as well as practical ways to eliminate it.
Contents
... | ['Feature Engineering', 'Beginners Guide', 'Dimensionality Reduction', 'Data Science', 'Machine Learning'] |
Genetic Algorithms for Natural Language Processing
Figure 1: genetic algorithm training a red square to avoid blue rectangles. Image by author.
“Data preparation accounts for about 80% of the work of data scientists.“ — Forbes
NLP modeling projects are no different — often the most time-consuming step is wrangling d... | ['Feature Engineering', 'Machine Learning', 'Genetic Algorithm', 'Tokenization', 'NLP'] |
Table of Contents
Introduction Creating Time Features Summary References
Introduction
One of the most difficult parts of data science modeling is utilizing time. Time can be used in a variety of ways. There is time-series-specific modeling, but you can also look at time in a different way. We will be looking into th... | ['Feature Engineering', 'Data', 'Data Science', 'Towards Data Science', 'Machine Learning'] |
In data science, especially with machine learning, asking the right questions guides you to valuable solutions. Sometimes, however, there is more than one question to answer or different points of view caused by contradictory or uncertain answers to those questions. I call these “multiple-component” problems. The chall... | ['Ensemble Learning', 'Feature Engineering', 'Data Science', 'Machine Learning', 'Domain Knowledge'] |
Feature Engineering for Categorical Data
Photo by Alex Motoc on Unsplash
In machine learning, features refer to the inputs to machine learning models or numerical representations of raw data. There two main types of features in tabular data: numerical feature and categorical feature. Feature engineering is a process ... | ['Categorical Data', 'Feature Engineering'] |
6 Reasons to Spend More Time Thinking About Labels
by Chikilino via pixabay
Imagine you are in a forest and can only get home by looking at markers labeled “may be closer to home”. You probably would take a while to get out of the forest.
That is, in essence how an artificial intelligence project may start out. Ofte... | ['Feature Engineering', 'Data Science', 'Data Cleaning', 'Machine Learning', 'Mlops'] |
Stacked Autoencoders.
Photo by Mika Baumeister on Unsplash
Dimensionality reduction
While solving a data science problem, did you ever come across a dataset with hundreds of features? or perhaps a thousand features? If no, then you don’t know how challenging it can be to develop an efficient model. Dimensionality re... | ['Feature Engineering', 'Data Analysis', 'Dimensionality Reduction', 'Data Science', 'Deep Learning'] |
K-Means tricks for fun and profit
Prologue
This will be a pretty small post, but an interesting one nevertheless.
K-Means is an elegant algorithm. It’s easy to understand (make random points, move them iteratively to become centers of some existing clusters) and works well in practice. When I first learned about it,... | ['Feature Engineering', 'Clustering', 'Data Science', 'Artificial Intelligence', 'Machine Learning'] |
Photo by Joshua Aragon on Unsplash
In this series of articles, we’re not just going to learn about how to use NLP to solve real-world problems, but we’re also going to learn about the Maths behind these concepts. So that we can understand how these algorithms actually work.
Natural language processing (NLP) is a subf... | ['Feature Engineering', 'Coding', 'Data Science', 'Machine Learning', 'Naturallanguageprocessing'] |
Avada Kedavra (aka The Killing Curse) may be the most deadly curse of all but in this Muggle world, we have to deal with something much worse than that.
The Curse of Dimensionality
There is a particular species of Muggles also known as Data Scientists, who have to deal with this curse in their day to day job.
(Okay,... | ['Feature Engineering', 'Dimensionality Reduction', 'Python', 'Data Science', 'Machine Learning'] |
Starting a Machine Learning (ML) project from scratch is not easy especially when you’re a newbie. From my own experience here is a post about the different steps to build and kick-start such projects.
The idea of this post came from my friend Genelva, which I will like to thanks for asking me how can we start a ML pr... | ['Data', 'Machine Learning', 'Feature Engineering', 'Data Science'] |
Embeddings have pervaded the data scientist’s toolkit, and dramatically changed how NLP, computer vision, and recommender systems work. However, many data scientists find them archaic and confusing. Many more use them blindly without understanding what they are. In this article, we’ll deep dive into what embeddings are... | ['Feature Engineering', 'Word Embeddings', 'Artificial Intelligence', 'Machine Learning', 'Mlops'] |
Feature Engineering Techniques
Feature engineering is one of the key steps in developing machine learning models. This involves any of the processes of selecting, aggregating, or extracting features from raw data with the aim of mapping the raw data to machine learning features.
Mapping raw data to feature vectors. (... | ['Feature Engineering', 'Feature Extraction', 'Vectorization', 'Data Science', 'One Hot Encoding'] |
Libraries
import random
from PIL import Image
import cv2
import numpy as np
from matplotlib import pyplot as plt
import json
import albumentations as A
import torch
import torchvision.models as models
import torchvision.transforms as transforms
import torch.nn as nn
from tqdm import tqdm_notebook
from torc... | ['Feature Engineering', 'Computer Vision', 'AI', 'Data Science', 'Machine Learning'] |
You can’t build a great building on a weak foundation. You must have a solid foundation if you’re going to have a strong super structure.
-Gordon B.Hinckley
Feature Engineering is the crucial module in the life cycle of a Data science project.
For instance, you are tasked with a gardening project and all you were pr... | ['Feature Engineering', 'Feature Scaling', 'Eda', 'Data Science', 'Machine Learning'] |
In this article, we’ll look at what Feature Engineering is and discuss some techniques used for feature engineering.
Feature
In machine learning and data science, a feature is an individual measurable property or characteristic of a phenomenon, usually in the form of structured columns. For instance, we have a simple... | ['Feature Engineering', 'Data Analysis', 'Python', 'Data Science', 'Machine Learning'] |
I was thinking about using machine learning to create a musical editor. I found a great dataset on kaggle.com, started to play around with it, and design the process. During my attempts, trying to use K-means clustering, with various conditional samplings, I stumbled upon a question — how do I measure feature importanc... | ['Cluster Analysis', 'Feature Engineering', 'Feature Importance', 'Clustering'] |
This is walkthrough of my case study and my approach on a research paper presented at the IEEE Conference, 2017. The authors of the paper have considered a real-world imbalanced dataset available on Kaggle’s competition Can you predict Product Backorders?.
We will delve deep into how material backorders can be minimiz... | ['Random Forest', 'AWS', 'Exploratory Data Analysis', 'Feature Engineering', 'Machine Learning'] |
Essential guide to perform Feature Binning using a Decision Tree Model
Image by Pete Linforth from Pixabay
Feature Engineering is an essential component of a machine learning model development pipeline. A machine learning model understands only numerical vectors, so a data scientist needs to engineer the features to ... | ['Feature Engineering', 'Data Science', 'Artificial Intelligence', 'Education', 'Machine Learning'] |
Item-Based Collaborative Filtering in Python
Photo by CardMapr.nl on Unsplash
Item-based collaborative filtering is the recommendation system to use the similarity between items using the ratings by users. In this article, I explain its basic concept and practice how to make the item-based collaborative filtering usi... | ['Movie Recommendation', 'Python', 'Collaborative Filtering', 'Item Based Cf', 'Recommendation System'] |
While working on ranking problems (feed ranking, search ranking etc.), I have often encountered situations when I needed to compare ranked lists generated by separate systems — for example Production v/s an A/B test. The need to compared two or more ranked lists is more common than you would think. Let’s consider a sim... | ['Editors Pick', 'Statistics', 'Machine Learning', 'Correlation', 'Recommendation System'] |
Erika Sun & Keshava Subramanya | Ads Intelligence Team
The Ads Intelligence team at Pinterest is charged with building and maintaining machine learning and algorithm-driven recommendations and the Recommendations Ranker to provide advertisers with the best experience in reaching relevant Pinners and help them reach th... | ['Computational Advertising', 'Machine Learning', 'Recommendation System'] |
RankNet
Model Target
Instead of modelling the score of each document one by one, RankNet proposed to model the target probabilities between any two documents (di & dj) of the same query.
And the target probabilities Pij of di and dj is defined as
1 if si > sj
0.5 if si=sj
0 if si < sj
where si and sj is the scor... | ['Information Retrieval', 'Learning To Rank', 'TensorFlow', 'Machine Learning', 'Recommendation System'] |
Recommendation engines are powerful tools that make browsing content easier. Moreover, a great recommendation system helps users find things they wouldn’t have thought to look for on their own. For these reasons, recommendation tools can dramatically boost e-commerce turnover. Here we show how we — at Decathlon France ... | ['NLP', 'Artificial Intelligence', 'TensorFlow', 'Recurrent Neural Network', 'Recommendation System'] |
Ranking Evaluation Metrics for Recommender Systems
Various evaluation metrics are used for evaluating the effectiveness of a recommender. We will focus mostly on ranking related metrics covering HR (hit ratio), MRR (Mean Reciprocal Rank), MAP (Mean Average Precision), NDCG (Normalized Discounted Cumulative Gain). Benj... | ['Mathematics', 'Machine Learning', 'Artificial Intelligence', 'Recommendation System'] |
1. LightFM
LightFM is a Python implementation of LightFM, a hybrid recommendation algorithm.
LightFM is a Python implementation of several popular recommendation algorithms for implicit and explicit feedback, including efficient BPR and WARP ranking losses. It’s easy to use, fast (via multithreaded model estimation) ... | ['Python', 'Data Science', 'Artificial Intelligence', 'Machine Learning', 'Recommendation System'] |
More than 1 and a half year ago, I wrote a blog post detailing the reason why I decided to stop improving TV Show Tracker 3 in order to focus on making a brand new TV Show Tracker from scratch. In a nutshell, the maintenance cost was too high and adding new features was nearly impossible as the code base was too old (a... | ['TV Shows', 'TV Series', 'Subscription', 'iOS App Development', 'Recommendation System'] |
Recommendation system paper challenge (2/50)
Paper Link
Why I write this blog?
The main reason is that I want to take some notes so that in the future, I can quickly recall it and do have to add so many favorite papers for that. Besides that, this paper is really great and popular!
Why this paper?
RecSys’10 and it... | ['Paper', 'Machine Learning', 'Recommendation System'] |
When a subclass of the information filtering system can predict the preferences or ratings that a user would give to an item or like, it is called a recommendation engine system. They are mostly used in the case of commercial applications.
They are used in a wide variety of areas, but most commonly recognized as playl... | ['Recommendations', 'Engine', 'Search', 'System', 'Recommendation System'] |
Understanding and Implementation of Apriori Algorithm with Python — Part 2
In the previous part click here. we learn how apriori algorithm work, basic intuition behind it. we also discuss support, confidence and lift. Now we will see how to implement apriori algorithm for large data set with python. Ishant Wadhwa Foll... | ['Apriori Algorithm', 'Implementation', 'Suport', 'Python', 'Recommendation System'] |
Orchestrating the model deployment with Kubeflow Pipelines
The tools and frameworks are identified to be able to perform a model deployment. Now we will need to define all the steps that will be required to execute a reliable model deployment. The required steps are, from a high-level point of view:
Deploy the new mo... | ['Kubernetes', 'Kubeflow Pipelines', 'Machine Learning', 'Production', 'Recommendation System'] |
In the e-commerce business you want to advertise smart. It also needs powerful analytics tool that can record customer’s interaction with their Website, App or Server and visualize the behavior at customer level. To advertise products smartly implies that it should be real time. In one of our projects we had to feed a ... | ['AWS', 'Snowplow', 'Data Pipeline', 'Kinesis', 'Recommendation System'] |
A location-based recommendation engine analyzes the data related to the user location along with other related data to generate more accurate recommendations.
Nowadays, the majority of the online platforms (apps and websites) are adopting location-based recommender systems for the customers. Food delivery, salon servi... | ['Alie', 'Recommendations', 'AI', 'Recommendation System', 'Business'] |
Our national pulse report
Here at DiUS, we’ve been talking with many companies about leveraging ML over the past five years and found most organisations want to adopt ML, yet this transformative technology is not being adopted at the rate it should be.
In fact, our experience has been that a great proportion of organ... | ['Computer Vision', 'AI', 'Artificial Intelligence', 'Machine Learning', 'Recommendation System'] |
Three types of a problem statement on recommendation systems.
Introduction
When we start to do a data science project, the first thing that we should always do is define the problem, or translate the business problem into a data science problem. It’s not only about dividing the big project into small parts, but also ... | ['Deep Learning', 'Machine Learning', 'Recommendation System'] |
Recommender Systems Based On Social Networks
The incorporation of social networks into a recommender system might make a major difference. Eduard Melu Follow Jun 17 · 10 min read
Recommender systems received a lot of attention in the scientific community but for a good reason …
They are incredibly practical and can ... | ['Knowledge Sharing', 'Big Data', 'Data Science', 'Social Network', 'Recommendation System'] |
Artificial intelligence (AI) technologies are penetrating various business domains from retail to space engineering. But human sensory experience projected into the art is still the area where no algorithm can compete with artists. However, AI comes in handy for music composing, creating streaming platforms, and moneti... | ['AI', 'Copyright', 'Artificial Intelligence', 'Spotify', 'Recommendation System'] |
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