Analytics Vidhya
MARCH 1, 2022
This article was published as a part of the Data Science Blogathon. Computer vision has advanced considerably but is still challenged in matching the precision of human perception. This article belongs to computer vision. Here we will learn from scratch. It can be challenging for beginners to distinguish between different related computer vision tasks.
David Menninger's Analyst Perspectives
MARCH 2, 2022
Natural language processing (NLP) is a field that combines artificial intelligence (AI), data science and linguistics that enables computers to understand, interpret and manipulate text or spoken words. NLP includes generating narratives based on a set of data values, using text or speech as inputs to access information, and analysing text or speech, for instance, to determine its sentiment.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Smart Data Collective
MARCH 1, 2022
AI technology is changing many aspects of modern business. More companies are using AI technology to automate their social media marketing strategies. We previously mentioned the benefits of using data analytics to make the most of social media marketing. However, AI is arguably even more important. Social media is a highly profitable way to market.
KDnuggets
MARCH 4, 2022
While there may always seem to be something new, cool, and shiny in the field of AI/ML, classic statistical methods that leverage machine learning techniques remain powerful and practical for solving many real-world business problems.
Advertisement
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
Analytics Vidhya
MARCH 4, 2022
This article was published as a part of the Data Science Blogathon. Introduction In this article, we will be predicting how engaging a video can be at the user level. We have been provided with a dataset that contains that user’s earlier videos engagement score along with their personal information. We will build multiple regression models […].
Dataiku
MARCH 3, 2022
There is a global push for digital transformation and taking an “innovation first” approach, but, up to 80% of these initiatives will fail. Organizations approach data science and analytics platforms with the expectation of large projects that provide large returns on investment. However, the success of small projects can have a much broader impact on company-wide technology adoption.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
KDnuggets
MARCH 4, 2022
How do you keep up with all the news and trends, and navigate through the endless stream of AI information? Check out this author's list of favorite AI papers sources that help you float effortlessly in the info ocean.
Analytics Vidhya
MARCH 4, 2022
This article was published as a part of the Data Science Blogathon. Introduction As most of us are doing our jobs or attending school/college virtually, we often have to attend online meetings and we can’t expect each of our places to always be quiet. Some of us may live in a noisy environment where we can […]. The post Audio Denoiser: A Speech Enhancement Deep Learning Model appeared first on Analytics Vidhya.
Juice Analytics
MARCH 4, 2022
March is Women’s History Month and as a company that celebrates women, we wanted to highlight some of the most influential women in the history of data visualization! So let us introduce you to some of these incredible women who have shaped the industry we all love and are committed to pushing forward. Florence Nightingale: Florence Nightingale is considered to be one of the first pioneers of data visualization.
Smart Data Collective
MARCH 2, 2022
Data science is a growing profession. While it involves more opportunities than ever, it also has a lot more complications. Standards and expectations are rapidly changing, especially in regards to the types of technology used to create data science projects. Most data scientists are using some form of DevOps interface these days. One of the most popular is Kubernetes.
Advertisement
📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.
KDnuggets
MARCH 2, 2022
Analysts predict an AI boom, driven by possibilities and record funding. While challenges remain, a hybrid approach combining the best of the realm may finally send it sailing into the mainstream.
Analytics Vidhya
MARCH 3, 2022
This article was published as a part of the Data Science Blogathon. Introduction The Tensorflow framework is an open end-to-end machine learning platform. It’s a symbolic math toolkit that integrates data flow and differentiable programming to handle various tasks related to deep neural network training and inference. It enables programmers to design machine learning applications utilising […].
Dataiku
MARCH 4, 2022
Since the Spanish flu, countries around the globe have established government organizations and departments of health in order to implement public health mandates and coordinate and manage national health responses during times of crisis (i.e., the global health crisis that began in 2020 or natural disasters such as droughts, bushfires, and floods, among others).
Smart Data Collective
MARCH 3, 2022
There is no question that data has become a valuable asset to almost every organization. Companies use big data to optimize their marketing strategies, maintain better relationships with their customers, manage their financial strategies and improve human resources capabilities. Unfortunately, data isn’t always easy to manage. You need to rely on the services of a well trained specialist that understands the nuances of big data technology.
Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com
Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.
KDnuggets
MARCH 3, 2022
In the Cybersecurity sector Adversarial machine learning attempts to deceive and trick models by creating unique deceptive inputs, to confuse the model resulting in a malfunction in the model. .
Analytics Vidhya
MARCH 3, 2022
This article was published as a part of the Data Science Blogathon. Introduction The activation function is defined as follows: The activation function calculates a weighted total and then adds bias to it to decide whether a neuron should be activated or not. The Activation Function’s goal is to introduce non-linearity into a neuron’s output.
Cloudera
MARCH 3, 2022
Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance. In 2019, the U.K.’s Information Commissioner’s Office fined Marriott International over £99 million ($136 million) for violating the General Data Protection Regulation (GDPR), a European law govern
Smart Data Collective
MARCH 2, 2022
Data science is an evolving profession. Artificial intelligence is also changing at a remarkable pace. A number of new platforms and tools are being regularly rolled out to help data scientists do their jobs more effectively and easily. Savvy data scientists and AI developers are keeping up with trends and learning the new technology that can help them work more efficiently.
Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
KDnuggets
MARCH 1, 2022
Many companies have been capturing customer data in some form or another for decades. Petabytes of data are traversing networks worldwide every day, and all of that data means big money. Here's how companies can best utilize this data to influence positive outcomes.
Analytics Vidhya
MARCH 2, 2022
This article was published as a part of the Data Science Blogathon. What is Convolutional Neural Network? Convolutional Neural Networks also known as CNNs or ConvNets, are a type of feed-forward artificial neural network whose connectivity structure is inspired by the organization of the animal visual cortex. Small clusters of cells in the visual cortex are […].
TDAN
MARCH 1, 2022
This article is the third in a series taking a deep dive on how to do a current state analysis on your data. This article focuses on data culture, what it is, why it is important, and what questions to ask to determine its current state. The first two articles focused on data quality and data […].
Smart Data Collective
FEBRUARY 28, 2022
We are all in awe of the changes that big data has created for almost every industry. The implications of big data is more obvious in some industries than others. For example, we can all appreciate the tremendous changes that data science has created for the financial industry, healthcare and web design. The impact developments in data technology have had on other industries have gotten far less publicity, but that doesn’t mean it hasn’t been significant.
Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.
KDnuggets
MARCH 3, 2022
This article will solely focus on learning linear algebra, as it forms the backbone of machine learning model implementation.
Analytics Vidhya
FEBRUARY 26, 2022
This article was published as a part of the Data Science Blogathon. Introduction Data Augmentation (DA) Technique is a process that enables us to artificially increase training data size by generating different versions of real datasets without actually collecting the data. The data needs to be changed to preserve the class categories for better performance in […].
TDAN
MARCH 1, 2022
Why Differential Privacy Overcomes Many of the Fatal Flaws of De-Identification and Data Masking If data is the new oil, then privacy is the new environmentalism. With the growing use of data comes the need for strong privacy protections. Indeed, robust data privacy protects against rogue employees spying on users (like these at Uber or Google) or even well-meaning employees who have […].
Smart Data Collective
MARCH 4, 2022
Running a small business can be difficult; you have to do multiple things simultaneously – and sometimes it’s not enough. However, technology proves to be handy when it comes to streamlining things and helping you save money and time. In fact, most successful companies depend on technology for almost every aspect of their businesses. And while there are many types of technology available, choosing to go digital does not have to be a headache.
Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage
Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.
KDnuggets
MARCH 1, 2022
Also: Decision Tree Algorithm, Explained; The Complete Collection of Data Science Cheat Sheets – Part 1; Essential Machine Learning Algorithms: A Beginner’s Guide; An Easy Guide to Choose the Right Machine Learning Algorithm.
Analytics Vidhya
MARCH 1, 2022
This article was published as a part of the Data Science Blogathon. There are immense computational costs of Deep Learning and AI. Artificial intelligence algorithms, which power some of technology’s most cutting-edge applications, such as producing logical stretches of text or creating visuals from descriptions, may need massive amounts of computational power to train.
Depict Data Studio
FEBRUARY 28, 2022
Andrew Forsman is a Depict Data Studio student and self-described “data viz nerd” who has over 10 years of experience helping organizations plan for, execute, and learn from research and evaluations. Andrew’s sharing examples of slider plots and step-by-step instructions for making them in Excel. Thanks for sharing, Andrew! –Ann. — Hey everyone!
Jet Global
FEBRUARY 28, 2022
Financial professionals in real estate contend with a wide array of responsibilities—managing financial statements, office space floors, signage, storage space, land, and more. Regulations and interest rates are in a state of constant flux, and they must be assessed as changes arise to build accurate reports. Not only is it time consuming to dump data into spreadsheets and reformat as information changes, but it’s also difficult to consolidate financials when multiple properties are involved.
Speaker: Jesse Simms, VP at Giant Partners
This new, thought-provoking webinar will explore how even incremental efforts and investments in your data can have a tremendous impact on your direct mail and multi-channel marketing campaign results! Industry expert Jesse Simms, VP at Giant Partners, will share real-life case studies and best practices from client direct mail and digital campaigns where data modeling strategies pinpointed audience members, increasing their propensity to respond – and buy.
Expert insights. Personalized for you.
359 
Let's personalize your content