Analytics Vidhya

DECEMBER 4, 2022

Introduction The global financial crisis of 2007 has had a long-lasting effect on the economies of many countries. In the epic financial and economic collapse, many lost their jobs, savings, and much more. When too much risk is restricted to very few players, it is considered as a notable failure of the risk management framework. […]. The post XAI: Accuracy vs Interpretability for Credit-Related Models appeared first on Analytics Vidhya.

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AssemblyAI

DECEMBER 23, 2022

ChatGPT is the latest language model from OpenAI and represents a significant improvement over its predecessor GPT-3. Similarly to many Large Language Models, ChatGPT is capable of generating text in a wide range of styles and for different purposes, but with remarkably greater precision, detail, and coherence. It represents the next generation in OpenAI's line of Large Language Models, and it is designed with a strong focus on interactive conversations.

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AI Impacts

DECEMBER 22, 2022

Harlan Stewart and Katja Grace* , 22 December, 2022 News New Hires and role changes In 2022, the AI Impacts team has grown from two to seven full time staff. Out of more than 250 applicants, we hired Elizabeth Santos as Operations Lead, Harlan Stewart as Research Assistant, and three Research Analysts: Zach Stein-Perlman, Aysja Johnson, and (are in the process of hiring) Jeffrey Heninger.

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IBM Journey to AI blog

DECEMBER 16, 2022

Imagine walking into the largest library you’ve ever seen. You have a specific book in mind, but you have no idea where to find it. Fortunately, the library has a computer at the front desk you can use to search its entire inventory by title, author, genre, and more. You enter the title of the book into the computer and the library’s digital inventory system tells you the exact section and aisle where the book is located.

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Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. These data science teams are seeing tremendous results—millions of dollars saved, new customers acquired, and new innovations that create a competitive advantage. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

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Analytics Vidhya

DECEMBER 15, 2022

This article was published as a part of the Data Science Blogathon. Introduction Generally, machine learning can be classified into four types: supervised machine learning, unsupervised machine learning, semi-supervised machine learning, and reinforcement learning. Supervised machine learning is a type of machine learning that is the easiest and less complex type or branch of data science. […].

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AssemblyAI

DECEMBER 22, 2022

Developments in AI are moving at breakneck speed. From generative AI to Large Language Models to Transformers, a new golden age of AI research is powering some of today’s most innovative technologies. Not surprisingly, AI-first companies, where AI is integral to the company’s product or platform, are increasingly coming to market and outstripping their competition.

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Cassie Kozyrkov

DECEMBER 7, 2022

The Revolutionary New Tool for Conversation Generation Continue reading on HackerNoon.

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AWS Machine Learning Blog

DECEMBER 29, 2022

Last year, we announced the general availability of RStudio on Amazon SageMaker , the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale.

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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?

Generative AI

Machine Learning Mastery

DECEMBER 30, 2022

Last Updated on December 30, 2022 Logistic regression is a type of regression that predicts the probability of an event. It is used for classification problems and has many applications in the fields of machine learning, artificial intelligence, and data mining. The formula of logistic regression is to apply a sigmoid function to the output […] The post Building a Logistic Regression Classifier in PyTorch appeared first on MachineLearningMastery.com.

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Eugene Yan

DECEMBER 10, 2022

A quick overview of variational and denoising autoencoders and comparing them to diffusers.

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Analytics Vidhya

DECEMBER 4, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will be seeing MLOps from the dimension of one of the powerful tools that make it easy to implement. These tool help to improve the deployment process for robust machine-learning projects. We will start by briefly seeing MLOps […]. The post Explaining MLOps using MLflow Tool appeared first on Analytics Vidhya.

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AssemblyAI

DECEMBER 15, 2022

Last weekend, AssemblyAI held our first-ever hackathon. With the AssemblyAI $50k Winter Hackathon , we hoped to foster creativity in building AI-first products. During the hackathon, 440 participants from 84 countries worked hard to build over 150 projects. With so many great projects to choose from, it was hard to narrow them down to the winners. We were incredibly blown away by the quality and quantity of submissions and want to congratulate all of the hackers that came together with us to cre

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Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Cassie Kozyrkov

DECEMBER 21, 2022

Will AI fully exit the realm of science fiction and begin to change everything?

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Google Research AI blog

DECEMBER 16, 2022

Posted by Tal Schuster, Research Scientist, Google Research Language models (LMs) are the driving force behind many recent breakthroughs in natural language processing. Models like T5 , LaMDA , GPT-3 , and PaLM have demonstrated impressive performance on various language tasks. While multiple factors can contribute to improving the performance of LMs, some recent studies suggest that scaling up the model’s size is crucial for revealing emergent capabilities.

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Machine Learning Mastery

DECEMBER 30, 2022

Last Updated on December 30, 2022 In the previous session of our PyTorch series, we demonstrated how badly initialized weights can impact the accuracy of a classification model when mean square error (MSE) loss is used. We noticed that the model didn’t converge during training and its accuracy was also significantly reduced. In the following, […] The post Training Logistic Regression with Cross-Entropy Loss in PyTorch appeared first on MachineLearningMastery.com.

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AWS Machine Learning Blog

DECEMBER 29, 2022

The last decade of the Industry 4.0 revolution has shown the value and importance of machine learning (ML) across verticals and environments, with more impact on manufacturing than possibly any other application. Organizations implementing a more automated, reliable, and cost-effective Operational Technology (OT) strategy have led the way, recognizing the benefits of ML in predicting assembly line failures to avoid costly and unplanned downtime.

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Analytics Vidhya

DECEMBER 3, 2022

This article was published as a part of the Data Science Blogathon. Introduction From the current trends in technology, a lot is likely to become more sophisticated. One area we will look at is the new technology known as Vyper, which is a programming language for developing apps on the web 3. This type of […]. The post A Guide to Vyper and its Environments appeared first on Analytics Vidhya.

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AssemblyAI

DECEMBER 14, 2022

Today, we're excited to announce our new v9 transcription model. The v9 model marks one of our biggest improvements to date and shows increased performance across the board on many audio types compared to our v8 model. The v9 model also provides the foundation for our v10 model, which our AI research team is already working on for release in early 2023.

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Cassie Kozyrkov

DECEMBER 24, 2022

The year that changed the way we work Continue reading on The Startup »

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Google Research AI blog

DECEMBER 13, 2022

Posted Keerthana Gopalakrishnan and Kanishka Rao, Google Research, Robotics at Google Major recent advances in multiple subfields of machine learning (ML) research, such as computer vision and natural language processing, have been enabled by a shared common approach that leverages large, diverse datasets and expressive models that can absorb all of the data effectively.

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Speaker: Jay Black, Senior Account Executive

Let's set the record straight: in-store retail isn't dead - it's evolving! Faced with the digital age and the demands of omnichannel shopping, some retailers are thriving while others are struggling to adapt. Join Jay Black in this exclusive session as he explores the strategies that set successful stores apart, including: Crafting unique and unforgettable in-store experiences 🛍️ Mastering the art of retail demands 🛒 Navigating inventory challenges in today's climate 📦 an

DeepMind

DECEMBER 5, 2022

Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and communication – and we can learn a lot from playing them. In our recent paper, published today in Nature Communications, we show how artificial agents can use communication to better cooperate in the board game Diplomacy, a vibrant domain in artificial intelligence (AI) research,

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Machine Learning Mastery

DECEMBER 31, 2022

Last Updated on January 1, 2023 While a logistic regression classifier is used for binary class classification, softmax classifier is a supervised learning algorithm which is mostly used when multiple classes are involved. Softmax classifier works by assigning a probability distribution to each class. The probability distribution of the class with the highest probability is […] The post Introduction to Softmax Classifier in PyTorch appeared first on MachineLearningMastery.com.

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Analytics Vidhya

DECEMBER 4, 2022

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction The real-world data can be very messy and skewed, which can mess up the effectiveness of the predictive model if it is not addressed correctly and in time. The consequences of skewness become more pronounced when a large model is […]. The post Comparison of Text Generations from GPT and GPT-2 appeared first on Analytics Vidhya.

Data Science 369

Data Science NLP Python 369

AssemblyAI

DECEMBER 11, 2022

Sales, marketing, and customer success teams need end-to-end deal visibility to win in today’s hypercompetitive market. Intelligent call coaching features, powered by top revenue intelligence platforms, can help by providing sales and support representatives with call-specific insights and guidance that aid interactions with customers and leads.

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Data Analysis

PyImageSearch

DECEMBER 29, 2022

Grooming is taking your product’s to-do list of work and transforming it into a product backlog. If you’d like to learn how to groom or refine your backlog so you’re ready for your Sprint, just keep reading. Grooming your backlog Let’s start with a quick working definition. Grooming, also known as refinement in Scrum, is taking notional work and clarifying the scope, testing, and effort estimates associated with that work until it is ready to turn over to the developers t

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Google Research AI blog

DECEMBER 14, 2022

Posted by Quan Wang, Senior Staff Software Engineer, and Fan Zhang, Staff Software Engineer, Google In 2019 we launched Recorder , an audio recording app for Pixel phones that helps users create, manage, and edit audio recordings. It leverages recent developments in on-device machine learning to transcribe speech , recognize audio events , suggest tags for titles, and help users navigate transcripts.

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DeepMind

DECEMBER 5, 2022

Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and communication – and we can learn a lot from playing them. In our recent paper, published today in Nature Communications, we show how artificial agents can use communication to better cooperate in the board game Diplomacy, a vibrant domain in artificial intelligence (AI) research,

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Artificial Intelligence Artificial Intelligence AI Researcher AI Research 57