The Litterati app has been around for a couple years on iOS + Android. Over that time, well over 100k people have downloaded the app and been a part of a global team that is 'crowdsource cleaning the Earth'.
Over that time, people only had access to the data that they themselves generated.
An easy, automated, repeatable way to check your data science solution is doing exactly what it's designed to do.
Data is a central piece of the climate change debate. With the climate change datasets on this list, many data scientists have created visualizations and models to measure and track the change in surface temperatures, sea ice levels, and more. Many of these datasets have been made public to allow people to contribute and add valuable insight into the way the climate is changing and its causes.
One of the trickiest situations in machine learning is when you have to deal with datasets coming from different time scales.
For digital nomads, college students, stay-at-home parents or anyone looking for remote work positions, this article introduces online/remote work positions that are available today in the fields of AI Data Collection and Data Annotation.
For those looking to build predictive models, this article will introduce 10 stock market and cryptocurrency datasets for machine learning.
Hugging Face offers solutions and tools for developers and researchers. This article looks at the Best Hugging Face Datasets for Building NLP Models.
Tableau
A Lazy Introduction to AI for Infosec.
In this article, I would like to share my own experience of developing a smart camera for cyclists with an advanced computer vision algorithm
Data is very important in building computer vision models and these are the 10 Biggest Datasets for Computer Vision.
The long-term success of an AI-based product relies on having the infrastructure for scalable, flexible, and cost-effective data labeling for its learning.
To understand the concept of data catalog, we need an assessment of the fundamentals that constitute the process on an elementary level. At the most rudimentary stage lies the idea of arrangement and the order of things.
This article focuses on the 14 Best Tableau Datasets for Practicing Data Visualization, which is essential for business analysts and data scientists.
For those looking to analyze crime rates or trends over a specific area or time period, we have compiled a list of the 16 best crime datasets made available for public use.
On Hacker Noon, I will be sharing some of my best-performing machine learning articles. This listicle on datasets built for regression or linear regression tasks has been upvoted many times on Reddit and reshared dozens of times on various social media platforms. I hope Hacker Noon data scientists find it useful as well!
When it comes to building an Artificially Intelligent (AI) application, your approach must be data first, not application first.
If you haven’t heard of the Universal Data Tool, it’s an open-source web or desktop program to collaborate, build and edit text, image, video and audio datasets with labels and annotations. You can get started with the Universal Data Tool at universaldatatool.com
WHAT IS DATA ANALYTICS?
Everything you need to know to automate, optimize and streamline the data collection process in your organization!
With torchvision datasets, developers can train and test their machine learning models on a range of tasks, such as image classification and object detection.
Is Python really the easiest and most efficient way to scrape a website? There are other options out there. Find out which one is best for you!
Text classification datasets are used to categorize natural language texts according to content. For example, think classifying news articles by topic, or classifying book reviews based on a positive or negative response. Text classification is also helpful for language detection, organizing customer feedback, and fraud detection. Though time consuming when done manually, this process can be automated with machine learning models. The result saves companies time while also providing valuable data insights.
This article looks at the Best Keras Datasets for Building and Training Deep Learning Models, accessible to developers and researchers worldwide.
Building a biomedical knowledge graph using publicly available datasets to better aid disease research and biomedical data modelling.
An image dataset contains specially selected digital images intended to help train, test, and evaluate an artificial intelligence (AI) or machine learning (ML)
¿Alguna vez te sucede cuando la gente te pide que escribas una API separada para integrar datos de redes sociales y guardar los datos sin procesar en tu base de datos de análisis en el sitio? Definitivamente quieres saber qué es la API, cómo se usa en web scraping y qué puede lograr con ella. Echemos un vistazo.
Scientists use geospatial analytics to build visualizations such as maps, graphs and cartograms. These are the Best Public Datasets for Geospatial Analytics.
In this post, I wanted to share a Reddit dataset list that gained a lot of traction on social media when it was first posted.
To help you build object recognition models, scene recognition models, and more, we’ve compiled a list of the best image classification datasets. These datasets vary in scope and magnitude and can suit a variety of use cases. Furthermore, the datasets have been divided into the following categories: medical imaging, agriculture & scene recognition, and others.
PyTorch has gained a reputation as a research-focused framework, and these are the Best PyTorch Datasets for Building Deep Learning Models available today.
An effective chatbot requires a massive amount of training data in order to quickly solve user inquiries without human intervention. However, the primary bottleneck in chatbot development is obtaining realistic, task-oriented dialog data to train these machine learning-based systems.
Human behaviour describes how people interact and in this article, we will look at the 8 Best Human Behaviour Datasets for Machine Learning.
In a real-world setting, you often only have a small dataset to work with. Models trained on a small number of observations tend to overfit and produce inaccurate results. Learn how to avoid overfitting and get accurate predictions even if available data is scarce.
R programming is mostly used in statistical analysis and ML.
This article looks at the Best Pre-Installed R Datasets Commonly Used for Statistical Analysis.
Have you ever experienced an itch you just can’t scratch? If yes, then you will feel my pain. A few days back, everything was fine, I was happily writing code(!) and doing standup meetings regularly. Just before the weekend, my boss called me and shared this problem with me.
Data is everywhere: whether you choose a new location for your business or decide on the color to use in an ad, data is an invisible advisor that helps make impactful decisions. With quite a number of resources to choose from, data is becoming more accessible, day by day. But as soon as it has been collected, one inevitable question arises: how do I turn this data into insights that can be acted upon?
Intro
In order to understand how a certain metric varies over time and to predict future values, we will look at the 10 Best Datasets for Time Series Analysis.
Web scraping has broken the barriers of programming and can now be done in a much simpler and easier manner without using a single line of code.
How Can You Sort Through Online Data?
This article on face recognition datasets is one of my best-performing articles I wrote originally on Lionbridge AI. I'm happy to share it with the Hacker Noon community!
Machine learning is an area of artificial intelligence (AI) and computer science that focuses on using data and algorithms to mimic the way humans learn
Excel is an indispensable tool for data manipulation, data visualization and statistical analysis. These are 15 Excel datasets for data analytics beginners.
While building a machine learning model, data scaling in machine learning is the most significant element through data pre-processing. Scaling may recognize the difference between a model of poor machine learning and a stronger one.
While building ScrapingBee I'm always checking different forums everyday to help people about web scraping related questions and engage with the community.
TLDR:
Aggregating into data lakes is the solution of today — but are Federated Sources the solution of tomorrow?
How to run a distributed data-mining operation to source and process crypto market data at zero cost.
Big data analytics can be applied for all and any business to boost their revenue and conversions and identify their common mistakes.
During the last couple of decades websites' functionally has increased dramatically - from simple landing pages serving simple static ads to complex progressive web apps whose functionality close to native applications including user authorization, location tracking, bluetooth handling, and offline mode.
Tables are a useful tool for visualizing, organizing and processing data in JavaScript. To start using them, you need to download a free library or one for a reasonable price. Here is a list of 10 useful, functional, and reliable JS libraries that will help you work with tables.
Computer vision enables computers to understand the content of images and videos. The goal in computer vision is to automate tasks that the human visual system can do.
A2D2, ApolloScape, and Berkeley DeepDrive are among the best autonomous driving datasets available today.
In 2022, Gartner named Microsoft Power BI the Business Intelligence and Analytics Platforms leader. These are the 13 Best Datasets for Power BI Practice.
These days we are all scared of the new airborne contagious coronavirus (2019-nCoV). Even if it is a tiny cough or low fever, it might underlie a lethargic symptom. However, what is the real truth?
Data extraction has many forms and can be complicated. From Preventing your IP from getting banned to bypassing the captchas, to parsing the source correctly, headerless chrome for javascript rendering, data cleaning, and then generating the data in a usable format, there is a lot of effort that goes in. I have been scraping data from the web for over 8 years. We used web scraping for tracking the prices of other hotel booking vendors. So, when our competitor lowers his prices we get a notification to lower our prices to from our cron web scrapers.
Previously published at https://www.octoparse.es/blog/15-preguntas-frecuentes-sobre-web-scraping
The emergence of technology is playing an inevitable role in business. It’s drastically transforming the way people work together in an organization. Both these technologies are revolutionizing every aspect of our life. These technologies are creating a culture where the collaboration of IT leaders and businesses results in realizing values from all generated data.
Introduction
In this test we use the data collection of 1.1M Hacker News curated comments with numeric fields from https://zenodo.org/record/45901.
Depth estimation and stereo image super-resolution are well-known tasks in the field of computer vision. To help researchers get high-quality training data for these tasks, industry-leading lightfield hardware provider Leia Inc. used their social media app, Holopix™, to create Holopix50k, the world’s largest “in-the-wild” stereo image dataset.
There is a great demand for data scientists presenting market dynamics that are favourable for the community. More so than your peers in other professions, you will be able to evaluate a company for what it is able to offer you, rather than solely being the one that is being evaluated. So what should you look for when comparing and evaluating data science roles? Here is a list of some commonly known factors plus some less discussed ones that will help you in your evaluation.
Introduction
It is often very difficult for AI researchers to gather social media data for machine learning. Luckily, one free and accessible source of SNS data is Twitter.
Speech-to-text (STT), also known as automated-speech-recognition (ASR), has a long history and has made amazing progress over the past decade. Currently, it is often believed that only large corporations like Google, Facebook, or Baidu (or local state-backed monopolies for the Russian language) can provide deployable “in-the-wild” solutions.
The resurgence of SQL-based RDBMS
This Slogging thread by and Arthur Tkachenko occurred in slogging's official #programming channel, and has been edited for readability.
Encoding is a technique used to convert categorical data to numerical representations to be able to use the data in machine learning algorithms.
Just over a week, most of you would have heard that Facebooks AI research team (FAIR) developed a neural transcompiler, that converts code from high level programming language like C++, Python, Java, Cobol into another language using ‘unsupervised translation’ . The traditional approach had been to tokenize the source language and convert it into an Abstract Syntax Tree (AST) which the transcompiler would use to translate to the target language of choice, based on handwritten rules that define the translations, such that abstract or the context is not lost.
An essential part of my company's Machine Learning team is working with different food datasets, and we spend a lot of time before for searching, combining or intersecting different datasets to get data that we need and can use in our work. Given that it might help someone else, I decided to list all helpful datasets in one place.
Сreate a model for the gender prediction based on the list of installed applications on a mobile device.
Scatter plots are a great way to visualize data. Data is represented as points on a Cartesian plane where the x and y coordinate of each point represents a variable. These charts let you investigate the relationship between two variables, detect outliers in the data set as well as detect trends. They are one of the most commonly used data visualization techniques and are a must have for your data visualization arsenal!
Photo by Evgeni Tcherkasski on Unsplash
A list of African language datasets from across the web that can be used in numerous NLP tasks.
