Analytics Vidhya
NOVEMBER 12, 2021
This article was published as a part of the Data Science Blogathon This article starts by discussing the fundamentals of Natural Language Processing (NLP) and later demonstrates using Automated Machine Learning (AutoML) to build models to predict the sentiment of text data. Other applications of NLP are for translation, speech recognition, chatbot, etc.
KDnuggets
NOVEMBER 8, 2021
With a lot of excitement and research around NLP, there are growing opportunities to apply these technologies to real-world scenarios. It's not trivial to become familiar with NLP and these open-source data sets can help you increase your skills.
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Dataconomy
NOVEMBER 9, 2021
The world has come to rely on data. Data-driven analytics fuel marketing strategies, supply chain operations, and more, and often to impressive results. However, without careful attention to data accuracy, these analytics can steer businesses in the wrong direction.
Smart Data Collective
NOVEMBER 12, 2021
One of the best things about digital marketing is that it’s often at the forefront of the latest online technologies. It doesn’t get any more cutting-edge at the moment than machine learning, and it’s not only large companies that have already started to take advantage. As far back as 2018, a veritable eternity in the world of online marketing, over 80% of marketing organizations reported the deployment or growth of their AI and machine learning efforts.
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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?
Analytics Vidhya
NOVEMBER 12, 2021
This article was published as a part of the Data Science Blogathon Introduction Hey all, I am sure you must have played pokemon games at some point in time and must have hated the issue of creating an optimal and balanced team to gain an advantage. What if I say one can do this by having […]. The post Optimizing Pokemon Team using Python’s PuLP Library appeared first on Analytics Vidhya.
KDnuggets
NOVEMBER 12, 2021
The PyTorch Deep Learning framework has a C++ API for use on mobile platforms. This article shows an end-to-end demo of how to write a simple C++ application with Deep Learning capabilities using the PyTorch C++ API such that the same code can be built for use on mobile platforms (both Android and iOS).
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Smart Data Collective
NOVEMBER 12, 2021
Much has changed since the time when organizations only knew of antiviruses and simple firewalls as the tools, they need to protect their computers. To address newer challenges, security providers have developed new technologies and strategies to combat evolving threats. Stephanie Benoit-Kurtz, Lead Area Faculty Chair for the University of Phoenix’s Cybersecurity Programs, offers a good summary of the changes security organizations should anticipate , especially in the time of the pandemic.
Analytics Vidhya
NOVEMBER 8, 2021
This article was published as a part of the Data Science Blogathon. Getting Started With… Natural Language Processing (NLP) is the field of artificial intelligence that relates lingual to Computer Science. I am assuming that you have understood the basic concepts of NLP. So we will move ahead. There are Some NLP applications as follows: […].
KDnuggets
NOVEMBER 9, 2021
In this article we are discussing that HDF5 is one of the most popular and reliable formats for non-tabular, numerical data. But this format is not optimized for deep learning work. This article suggests what kind of ML native data format should be to truly serve the needs of modern data scientists.
Tableau
NOVEMBER 12, 2021
Kristin Adderson. November 13, 2021 - 1:12am. November 13, 2021. Editor's note: This article originally appeared in Forbes , by Larissa Amoroso, Sr. Director, Tableau Community. In the journey to become data-driven, even data-leading, organizations traditionally viewed technology as the golden ticket. But adopting the right analytics platform isn’t enough: The ultimate accelerator of your data investments is community.
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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
NOVEMBER 12, 2021
According to the 2021 CMO Spend Survey by Gartner, budget allocation for marketing analytics failed to make the top 3 in priority falling behind digital commerce, marketing operations and brand strategy. While I understand that selling products, cutting costs and delivering brand strategy is important for long term business results, the lack of priority in using data troubles me.
Analytics Vidhya
NOVEMBER 11, 2021
This article was published as a part of the Data Science Blogathon INTRODUCTION Investing is an important part of one’s life because Investing helps in making the present and future safety, it allows you to grow financially. Also, investing is a process of compounding profits. Investing money at the right place and right time helps in increasing […].
KDnuggets
NOVEMBER 10, 2021
A machine can only understand numbers. As a result, converting text to numbers, called embedding text, is an actively researched topic. In this article, we review different word embedding techniques for converting text into vectors.
FlowingData
NOVEMBER 9, 2021
Over the years, more women have entered the workforce while the percentage of… Read More.
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
NOVEMBER 9, 2021
The average consumer is unaware of the phenomenal benefits that big data provides. One of the biggest benefits of big data is that it can help improve driver safety. Data analytics technology is becoming more useful when it comes to stopping traffic accidents. A lot of companies are sharing data to help make roads and vehicles safer, as well as helping drivers make better driving decisions on the road.
Analytics Vidhya
NOVEMBER 9, 2021
This article was published as a part of the Data Science Blogathon In this article, I am going to build multiple neural network models to solve a regression problem. Before we start working on the model, I would like to give a brief overview of what we will touch on and what steps we will follow. […]. The post Neural Network for Regression with Tensorflow appeared first on Analytics Vidhya.
KDnuggets
NOVEMBER 9, 2021
Beginners in the field can often have many misconceptions about machine learning that sometimes can be a make-it-or-break-it moment for the individual switching careers or starting fresh. This article clearly describes the ground truth realities about learning new ML skills and eventually working professionally as a machine learning engineer.
Tableau
NOVEMBER 12, 2021
Kristin Adderson. November 13, 2021 - 1:12am. November 13, 2021. Editor's note: This article originally appeared in Forbes , by Larissa Amoroso, Sr. Director, Tableau Community . In the journey to become data-driven, even data-leading, organizations traditionally viewed technology as the golden ticket. But adopting the right analytics platform isn’t enough: The ultimate accelerator of your data investments is community.
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.
Smart Data Collective
NOVEMBER 8, 2021
Data analytics has become a very important aspect of any modern business’s operating strategy. One of the most important ways to utilize big data is with financial management. The financial analytics market is projected to be worth $114 billion within the next two years. This is a testament to the amazing benefits it provides for companies in all sectors.
Analytics Vidhya
NOVEMBER 10, 2021
This article was published as a part of the Data Science Blogathon Image Source: Author Introduction to Fitness Tracker Market With the advancements in the IT domain, wearable devices have been in great demand in the recent past. A wearable device is simply a device that can be worn by the user and this device is […]. The post How To Use Python To Analyse Fitness Tracker Market: Step By Step EDA appeared first on Analytics Vidhya.
KDnuggets
NOVEMBER 11, 2021
The notion of self-service BI tools caught an expectation that they could provide a magic formula for easily helping everyone understand all the data. But, such an end-result isn't occurring in practice. To identify a better approach, we need to take a step back and determine what problem is actually trying to be solved.
Dataversity
NOVEMBER 12, 2021
Machine learning (ML) has enabled a whole host of innovations and new business models in fintech, driving breakthroughs in areas such as personalized wealth management, automated fraud detection, and real-time small business accounting tools. For a long time, one of the most significant challenges of machine learning has been the amount and quality of data […].
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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.
Smart Data Collective
NOVEMBER 10, 2021
Big data technology has been a huge gamechanger in the insurance sector. More insurance are using big data to assist with the underwriting process. They have discovered that data analytics has made the underwriting process a lot easier. They are getting a better understanding of risk and choosing rates for their policyholders. However, insurance companies aren’t the only ones affected by big data.
Analytics Vidhya
NOVEMBER 8, 2021
This article was published as a part of the Data Science Blogathon Overview of Linear Regression “Without understanding the engine, building or working with a car is just playing with metal” This seems to be true in almost all domains of life, without fundamentals; creation and innovation are simply not possible. In this guide, we will […].
KDnuggets
NOVEMBER 9, 2021
After a pause, we will be resuming KDnuggets Top Blog Rewards Program, starting with blogs published on KDnuggets in December. The program will be bigger, with $3,000 (USD) divided among top 8 most viewed guest blogs. Original blogs rewarded at the rate of 3X of reposts. Submit your original blog to KDnuggets first !
Dataversity
NOVEMBER 11, 2021
Back in 2020, when the COVID-19 pandemic was in its earliest, scariest stages, researchers found that localized search trends could predict outbreaks more accurately and quickly than other measures. User-generated inputs on the internet provided access to useful and actionable insights. All of the predictions had been garnered from Google Trends and similar search-engine-based tools.
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.
Smart Data Collective
NOVEMBER 10, 2021
These days, almost every organization relies on huge quantities of data to run day-to-day operations. There are times when projects may require you to convert or migrate data , depending on whether it’s moving from one system to another or from several databases into one. The terms “ database conversion ” and “database migration” are often used interchangeably, but they are two different processes that play a big role in an organization’s software implementation.
Analytics Vidhya
NOVEMBER 6, 2021
This article was published as a part of the Data Science Blogathon. Table of contents Introduction What is Microsoft Power BI? Microsoft Power BI Concepts Data sources in Microsoft Power BI Import Excel Data to Microsoft Power BI Query Editor Inbuilt visuals Conclusion Introduction There is so much data collected in businesses and industries today. […].
KDnuggets
NOVEMBER 9, 2021
OpenAI's latest research aims to solve math word problems. Let's dive a bit deeper into the ideas behind this new research.
Dataversity
NOVEMBER 12, 2021
A concise definition of data product was coined by DJ Patil as “a product that facilitates an end goal through the use of data.” This includes not only pure datasets, both raw and refined, but also products based heavily on algorithms, models, and similar data-intensive workloads. Leaders in data are leaders in business, and treating data as a product is […].
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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