KDnuggets
DECEMBER 23, 2021
Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.
Analytics Vidhya
DECEMBER 24, 2021
This article was published as a part of the Data Science Blogathon Introduction According to a report, 55% of businesses have never used a machine learning model before. Eighty-Five per cent of the models will not be brought into production. Lack of skill, a lack of change-management procedures, and the absence of automated systems are some […].
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Dataconomy
DECEMBER 24, 2021
The enterprise is investing heavily into multiple forms of AI, but interest in natural language processing (NLP) has gained momentum in the past few months. This is due in large part to the rise of chatbots and intelligent assistants in call centers, help desks, kiosks, and other customer support applications, but these are hardly.
Smart Data Collective
DECEMBER 22, 2021
Big data technology has become an invaluable asset to so many organizations around the world. There are a lot of benefits of utilizing data technology, such as improving financial reporting, forecasting marketing trends and efficient human resource allocation. It is crucial to business growth , as companies transition to more digital business models.
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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?
KDnuggets
DECEMBER 24, 2021
Feature selection methodologies go beyond filter, wrapper and embedded methods. In this article, I describe 3 alternative algorithms to select predictive features based on a feature importance score.
Analytics Vidhya
DECEMBER 21, 2021
This article was published as a part of the Data Science Blogathon Introduction Text classification is a machine-learning approach that groups text into pre-defined categories. It is an integral tool in Natural Language Processing (NLP) used for varied tasks like spam and non-spam email classification, sentiment analysis of movie reviews, detection of hate speech in social […].
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Smart Data Collective
DECEMBER 19, 2021
The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process. Likewise, Python is a popular name in the data preprocessing world because of its ability to process the functionalities in different ways.
KDnuggets
DECEMBER 20, 2021
XGBoost is an open-source implementation of gradient boosting designed for speed and performance. However, even XGBoost training can sometimes be slow. This article will review the advantages and disadvantages of each approach as well as go over how to get started.
Analytics Vidhya
DECEMBER 21, 2021
This article was published as a part of the Data Science Blogathon Introduction When data is collected, there is a need to interpret and analyze it to provide insight into it. This insight can be about patterns, trends, or relationships between variables. Data interpretation is the process of reviewing data through well-defined methods. They help assign meaning […].
FlowingData
DECEMBER 22, 2021
When you have many categories, use ridgelines to create an extremely compact visualization where you can easily identify major patterns and outliers. They are especially useful to display surges in mostly flat data series. Become a member for access to this — plus tutorials, courses, and guides.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
Smart Data Collective
DECEMBER 21, 2021
Big data is a phrase that the industry coined in 1987 , but it took years before it became truly popular. By the time the name was a household term, big data was everywhere, and companies were seeking ways to store and use the data. Data scientists knew that big data could hold valuable insights. The key was finding a way to analyze it as it continued to flood in constantly.
KDnuggets
DECEMBER 22, 2021
Start your learning journey in Reinforcement Learning with this first of two part tutorial that covers the foundations of the technique with examples and Python code.
Analytics Vidhya
DECEMBER 24, 2021
This article was published as a part of the Data Science Blogathon About Streamlit Streamlit is an open-source Python library that assists developers in creating interactive graphical user interfaces for their systems. It was designed especially for Machine Learning and Data Scientist team. Using Streamlit, we can quickly create interactive web apps and deploy them.
FlowingData
DECEMBER 22, 2021
The COVID-19 Online Visualization Collection is a project to catalog Covid-related graphics across countries, sources, and styles. They call it COVIC for short, which seems like a stretch for an acronym and a confusing way to introduce a project to people. But, it does categorize over 10,000 figures, which could be useful as a reference and historical context.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Smart Data Collective
DECEMBER 22, 2021
Artificial intelligence has become an invaluable form of technology for fostering better communications in the workplace. Artificial intelligence has been a beneficial changing force for many forms of communication technology. Video messaging is just one example. Video technology is becoming much more sophisticated. More video messaging services are dependent on data analytics, as the analytics in video market is growing over 20% a year.
KDnuggets
DECEMBER 20, 2021
Many real-world datasets consist of records of events that occur at arbitrary and irregular intervals. These datasets then need to be processed into regular time series for further analysis. We will use the AI & Analytics Engine to illustrate how you can prepare your time-series data in just 1 step.
Analytics Vidhya
DECEMBER 24, 2021
This article was published as a part of the Data Science Blogathon Introduction Time series data is the collection of data at specific time intervals like on an hourly basis, weekly basis. Stock market data, e-commerce sales data is perfect example of time-series data. Time-series data analysis is different from usual data analysis because you can […].
FlowingData
DECEMBER 23, 2021
Based on data from autonomous sensors floating in the oceans, researchers are able to model the flows and characteristics of ocean currents in more detail than ever before. For The New York Times, Henry Fountain and Jeremy White show how the shifts have unwelled centuries-old water deep in the ocean , which releases carbon into the air. The scrollytelling format of this piece works well to show sensor estimates over time.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Dataversity
DECEMBER 22, 2021
Trying to protect sensitive data was a major concern for the enterprise in 2021, and it will continue to be in the coming new year. Whether it be ransomware, a data breach, or a compliance fine associated with one of the new data regulations, the risk around an organization’s data is going to increase as its […]. The post What Data Protection Will Look Like in 2022 appeared first on DATAVERSITY.
KDnuggets
DECEMBER 21, 2021
Customizable, real-time data labeling pipelines that can continuously receive and process unlabeled data are necessary to train and perfect the AI that impacts our lives and daily conveniences.
Analytics Vidhya
DECEMBER 23, 2021
This article was published as a part of the Data Science Blogathon. Overview · Markovian Assumption states that the past doesn’t give a piece of valuable information. Given the present, history is irrelevant to know what will happen in the future. · Markov Chain is a stochastic process that follows the Markovian Assumption. · Markov chain […].
DataRobot
DECEMBER 20, 2021
The value of AI these days is undeniable. However, in a fast-changing environment, a decision made at the right time is critical. We collect more and more diverse data types, and we’re not always sure how we can turn this data into real value. Sometimes it takes hours and days of experimenting to get valuable insights. Or even if we have a pretty good understanding of the problem, there is not enough data to run a successful project and deliver impact back to the business.
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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.
Dataversity
DECEMBER 20, 2021
Reading Larry Burns’ “Data Model Storytelling” (TechnicsPub.com, 2021) was a really good experience for a guy like me (i.e., someone who thinks that data models are narratives). I agree with Larry on so many things. However, this post is not a review of Larry’s book. Read it for yourself – highly recommended. Reading it triggered […]. The post Tales of Data Modelers appeared first on DATAVERSITY.
KDnuggets
DECEMBER 21, 2021
If you have clear, well-defined objectives, it won’t be hard to identify the ETL technology that best meets your needs. Here are some of the best ETL tools you can use in your business.
Analytics Vidhya
DECEMBER 20, 2021
This article was published as a part of the Data Science Blogathon Introduction In the last article, we have discussed implementing the BERT model using the TensorFlow hub; you can read it here. Implementing BERT using the TensorFlow hub was tedious since we had to perform every step from scratch. First, we build our tokenizer, then […]. The post Multiclass Classification Using Transformers for Beginners appeared first on Analytics Vidhya.
FlowingData
DECEMBER 20, 2021
Zach Levitt and Bonnie Berkowitz for The Washington Post mapped and animated the natural and weather disasters from 2021. Differing from the 2019 version by Tim Meko, they framed it by month, which let them start with floods in January, through the storms in March, April, and May, to fires in July, up to the tornadoes in December. It was a rough year for many, only compounded by that virus.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.
Dataversity
DECEMBER 20, 2021
“Data is the currency of the future,” many experts have predicted. The 21st century has been characterized by the astounding amount of data we’ve gained access to. But what happens if this data isn’t properly stored? A data swamp begins to develop, and accessing that data becomes difficult and sometimes impossible. The internet, social media, […].
KDnuggets
DECEMBER 24, 2021
Check out these key development issues and tips learned from personal experience when deploying a TensorFlow-based image classifier Streamlit app on a Heroku server.
Analytics Vidhya
DECEMBER 20, 2021
This article was published as a part of the Data Science Blogathon Overview This article will discuss building a system that can detect malaria from cell images. The plan will be created in the form of a web application that can make it easier for users and even make it easier for developers who make […]. The post Malaria Cell Image Classification – An End-to-End Prediction appeared first on Analytics Vidhya.
FlowingData
DECEMBER 24, 2021
Many colleges use virtual proctoring software in an effort to reduce cheating on tests that students take virtually at home. But the software relies on facial recognition and assumptions about the proper testing environment. YR Media breaks down the flaws and even provides a simulation so that you can see what it’s like. Tags: bias , privacy , proctoring , YR Media.
Speaker: Anne Steiner and David Laribee
As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.
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