February, 2022

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Learn Mobile Price Prediction Through Four Classification Algorithms

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Mobile phones come in all sorts of prices, features, specifications and all. Price estimation and prediction is an important part of consumer strategy. Deciding on the correct price of a product is very important for the market success of a product. A new […]. The post Learn Mobile Price Prediction Through Four Classification Algorithms appeared first on Analytics Vidhya.

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Intelligence and Comprehension

O'Reilly Media

I haven’t written much about AI recently. But a recent discussion of Google’s new Large Language Models (LLMs), and its claim that one of these models (named Gopher) has demonstrated reading comprehension approaching human performance , has spurred some thoughts about comprehension, ambiguity, intelligence, and will. (It’s well worth reading Do Large Models Understand Us , a more comprehensive paper by Blaise Agüera y Arcas that is heading in the same direction.).

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Mailbag: How to Define a Data Team's Vision and Roadmap

Eugene Yan

I'm heading into a team lead role and would like to define the vision and roadmap.

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Accelerating fusion science through learned plasma control

DeepMind

Successfully controlling the nuclear fusion plasma in a tokamak with deep reinforcement learning

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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

Speaker: David Warren and Kevin O’Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

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Data Scientist Spotlight: Alex Tsourmas

DataRobot Blog

DataRobot is home to a treasure trove of Data Scientists. We’ve started a series called “Data Scientist Spotlight” as a way to meet the people behind the technology and introduce you to our great team. Introducing Alex Tsourmas. Alex works as a Customer-Facing Data Scientist within DataRobot’s Go-To-Market team, as the company continues to build its premier AI Cloud platform for organizations across the globe.

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Comparing R and Tableau for Data Visualisation

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. There has been a debate in the industry between R and Tableau. Which is better is the question. Let us see this in today’s article. Source – Author What is Data Visualization? Data visualization is an interdisciplinary field that uses visual elements […]. The post Comparing R and Tableau for Data Visualisation appeared first on Analytics Vidhya.

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How to change your order in 10,000 different ways

Bitext

How Synthetic Text can solve your training and evaluation problems for your virtual assistants / chatbots When shopping online, customers frequently have the need to modify their order: exchanging an item in the basket, deleting something already added… Customers ask for these kinds of changes in many different ways, like “how do I change my order?” or “I need to delete a product from my basket”.

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Red Flags to Look Out for When Joining a Data Team

Eugene Yan

What to consider for in terms of data, roadmap, role, manager, tooling, etc.

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Probing Image-Language Transformers for Verb Understanding

DeepMind

Multimodal Image-Language transformers have achieved impressive results on a variety of tasks that rely on fine-tuning (e.g., visual question answering and image retrieval). We are interested in shedding light on the quality of their pretrained representations--in particular, if these models can distinguish verbs or they only use the nouns in a given sentence.

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15 Modern Use Cases for Enterprise Business Intelligence

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?

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Picking the Right Notebook for Your Data Science Team

DataRobot Blog

The bar for AI keeps rising. Seventy-six percent of companies prioritize AI and machine learning (ML) over other IT initiatives, according to Algorithmia’s 2021 enterprise trends in machine learning report. With growing pressure on data scientists, every organization needs to ensure that their teams are empowered with the right tools. At the same time, the toolkit needs to meet enterprise needs and regulatory requirements.

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Stop paying for APIs to calculate distances and use this Open Source tool!

Applied Data Science

How to use OSRM to calculate distances reliably and for free. Photo by T.H. Chia on Unsplash Calculating distances between a set of coordinates is something that regularly comes up in Data Science projects. Whether it is planning routes for delivery services, or measuring a customer’s willingness to travel to certain locations, getting an accurate measure of distance is always key.

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Search Engines Using Deep Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. An end-to-end guide on building Information Retrieval system using NLP […]. The post Search Engines Using Deep Learning appeared first on Analytics Vidhya.

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Will AI Kill Your Job?

Kavita Ganesan

Oh, what will happen to our jobs when my company starts using AI? This is such a popular question that comes up when I give talks—even to a pseudo technical audience. Not surprisingly, this question will land sarcastic smiles on the faces of some data scientists and AI experts; you may even catch some eyes rolling. But it’s a valid question. Don’t forget, we had a US political candidate run for the presidency on the theme that automation is robbing people of good jobs and we should thus be compe

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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

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Solving (some) formal math olympiad problems

OpenAI

We built a neural theorem prover for Lean that learned to solve a variety of challenging high-school olympiad problems, including problems from the AMC12 and AIME competitions, as well as two problems adapted from the IMO.

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Probing Image-Language Transformers for Verb Understanding

DeepMind

Multimodal Image-Language transformers have achieved impressive results on a variety of tasks that rely on fine-tuning (e.g., visual question answering and image retrieval). We are interested in shedding light on the quality of their pretrained representations--in particular, if these models can distinguish verbs or they only use the nouns in a given sentence.

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Integrated Healthcare Means Integrated Data

DataRobot Blog

“Integrated healthcare” has become a bit of a buzzword as of late, but no one has settled on just one definition for the term. A 2016 paper that sought to explain integrated care , laid out four different definitions and five different conceptual frameworks. But if you break down these various definitions—and the hundreds of others that are out there— integrated care is collaborative and connected care.

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9 Biggest Benefits of Using AI in Your Retail Business

Dlabs.ai

In the retail industry, you must analyze data to achieve the best results. This is where AI technology can help, as it unlocks many opportunities to optimize almost every aspect of any retail business. This article will cover the nine biggest benefits of using AI in retail. And how it will positively impact your business, employees, customers, even the environment.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

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.

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Implementing Logistic Regression from Scratch using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Logistic Regression If you are here, you are already introduced to the concept of logistic regression and probably have had your hands dirty working on different datasets. The scikitlearn’s LogisticRegression is by far the best tool to use for any logistic regression […].

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Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 1: Self-training

The Stanford AI Lab Blog

Deep models require a lot of training examples, but labeled data is difficult to obtain. This motivates an important line of research on leveraging unlabeled data, which is often more readily available. For example, large quantities of unlabeled image data can be obtained by crawling the web, whereas labeled datasets such as ImageNet require expensive labeling procedures.

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Introducing spaCy Tailored Pipelines

Explosion

Explosion is pleased to announce a new development services offering, spaCy Tailored Pipelines. We’ll build you a custom natural language processing pipeline, delivered in a standardized format using spaCy’s projects system.

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Red Teaming Language Models with Language Models

DeepMind

In our recent paper, we show that it is possible to automatically find inputs that elicit harmful text from language models by generating inputs using language models themselves. Our approach provides one tool for finding harmful model behaviours before users are impacted, though we emphasize that it should be viewed as one component alongside many other techniques that will be needed to find harms and mitigate them once found.

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The Tumultuous IT Landscape Is Making Hiring More Difficult

After a year of sporadic hiring and uncertain investment areas, tech leaders are scrambling to figure out what’s next. This whitepaper reveals how tech leaders are hiring and investing for the future. Download today to learn more!

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DataRobot Explainable AI: Machine Learning Untangled

DataRobot Blog

In the past decade, we’ve seen an explosion in the usage of AI. From predicting which customers are likely to churn to forecasting inventory demand, businesses are adopting AI more and more frequently. With any AI solution , you want it to be accurate. But just as important, you want it to be explainable. It can be difficult to convince stakeholders at your organization to trust a model, even if it’s 90% accurate, if it’s unclear how a model arrives at decisions.

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Announcing GPT-NeoX-20B

Eleuther.ai

Announcing GPT-NeoX-20B, a 20 billion parameter model trained in collaboration with CoreWeave.

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A Comprehensive Guide on Hyperparameter Tuning and its Techniques

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s). Make it simple, for every […].

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Stanford AI Lab Papers and Talks at AAAI 2022

The Stanford AI Lab Blog

The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) is being hosted virtually from February 22th - March 1st. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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K-Fold Cross Validation Technique and its Essentials

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Image designed by the author Introduction Guys! Before getting started, just […]. The post K-Fold Cross Validation Technique and its Essentials appeared first on Analytics Vidhya.

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Emotions Using NLP | Based on Classifying Text

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Emotions are expressed through words, gestures, expressions, and with the ease of accessibility of social media today, emotions can now, also be expressed through tweets and Instagram/ WhatsApp stories. Through this article, we would try to analyze the underlying emotions of tweets posted […].

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Privacy-Preserving in Machine Learning (PPML)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview Machine learning (ML) has a lot of potential for increasing productivity. However, the quality of the data for training ML models should be excellent to provide good results. Any ML algorithm provides excellent performance only when there is huge and perfect data fed […].