Analytics Vidhya

NOVEMBER 15, 2022

This article was published as a part of the Data Science Blogathon. Introduction Hierarchical clustering is one of the most famous clustering techniques used in unsupervised machine learning. K-means and hierarchical clustering are the two most popular and effective clustering algorithms. The working mechanism they apply in the backend allows them to provide such a […].

Machine Learning 398

Machine Learning Algorithm Data Science Python 398

DeepMind

NOVEMBER 15, 2022

At DeepMind, our goal is to make sure everything we do meets the highest standards of safety and ethics, in line with our Operating Principles. One of the most important places this starts with is how we collect our data. In the past 12 months, we’ve collaborated with Partnership on AI (PAI) to carefully consider these challenges, and have co-developed standardised best practices and processes for responsible human data collection.

AI 57

AI AI 57

Bitext

NOVEMBER 14, 2022

Leveraging technology that generates text is coming to the main theaters and Forbes is the most recent one: “ The Biggest Opportunity In Generative AI Is Language, Not Images ” Different names are in use: generative AI, as in the article; synthetic text, following the popular term “synthetic data”; NLG (Natural Language Generation) is the most traditional term maybe not so trendy just for that reason.

Chatbots 52

Chatbots Generative AI AI AI 52

DataRobot Blog

NOVEMBER 15, 2022

Organizations are looking to deliver more business value from their AI investments, a hot topic at Big Data & AI World Asia. At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. A packed keynote session showed how repeatable workflows and flexible technology get more models into production.

Big Data 52

Big Data Explainability Data Science Data Scientist 52

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.

Analytics Vidhya

NOVEMBER 15, 2022

This article was published as a part of the Data Science Blogathon. Introduction Voting ensembles are the ensemble machine learning technique, one of the top-performing models among all machine learning algorithms. As voting ensembles are the most used ensemble techniques, there are lots of interview questions related to this topic that are asked in data […].

Machine Learning 398

Machine Learning Data Science Algorithm 398

Google Research AI blog

NOVEMBER 17, 2022

Posted by Mahima Pushkarna, Senior Interaction Designer, and Andrew Zaldivar, Senior Developer Relations Engineer, Google Research As machine learning (ML) research moves toward large-scale models capable of numerous downstream tasks, a shared understanding of a dataset’s origin, development, intent, and evolution becomes increasingly important for the responsible and informed development of ML models.

Metadata 45

Metadata ML Responsible AI Data Scientist 45

Julien Simon

NOVEMBER 17, 2022

In this video, I show you how to accelerate Transformer inference with Inferentia, a custom chip designed by AWS. Starting from a Hugging Face BERT model that I fine-tuned on AWS Trainium ([link] I compile it with the Neuron SDK for Inferentia. Then, using an inf1.6xlarge instance (4 Inferentia chips, 16 Neuron Cores), I show you how to use pipeline mode to predict at scale, reaching over 4,000 predictions per second at 3-millisecond latency ?

BERT 40

BERT Deep Learning 40

Analytics Vidhya

NOVEMBER 14, 2022

This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. Before DevOps, software development teams, quality assurance (QA) teams, security, and operations would test the code for several […].

DevOps 398

DevOps Software Development Data Science Machine Learning 398

Sebastian Ruder

NOVEMBER 14, 2022

Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. At the same time, a wave of NLP startups has started to put this technology to practical use.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics AI 52

Advertisement

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

Google Research AI blog

NOVEMBER 16, 2022

Posted by Yanqi Zhou, Research Scientist, Google Research, Brain Team The capacity of a neural network to absorb information is limited by the number of its parameters, and as a consequence, finding more effective ways to increase model parameters has become a trend in deep learning research. Mixture-of-experts (MoE), a type of conditional computation where parts of the network are activated on a per-example basis, has been proposed as a way of dramatically increasing model capacity without a pr

Algorithm 78

Algorithm Neural Network Natural Language Processing Computer Vision 78

Julien Simon

NOVEMBER 15, 2022

In this video, I show you how to accelerate Transformer inference with Optimum, an open source library by Hugging Face , and Intel OpenVINO. I start from a Vision Transformer model fine-tuned for image classification, and quantize it with OpenVINO. Running benchmarks on an AWS c6i instance (Intel Ice Lake architecture), we speed up the original model more than 20% and divide its size by almost 4, with just a few lines of simple Python code and just a tiny accuracy drop!

Python 40

Python Deep Learning Machine Learning 40

Analytics Vidhya

NOVEMBER 14, 2022

This article was published as a part of the Data Science Blogathon. Introduction Flutter where F stands for Front- end, L stands for Language, U stands for UI layout, T stands for Time, T stands for Tools, E stands for Enable, and R stands for Rich. In other words, Flutter is a tool used in […]. The post Building Our Applications Using Flutter appeared first on Analytics Vidhya.

Data Science 394

Data Science Python 394

AssemblyAI

NOVEMBER 15, 2022

This week’s AI Research Review is Git Re-Basin: Merging Models Modulo Permutation Symmetries. Git Re-Basin: Merging Models Modulo Permutation Symmetries What’s Exciting About this Paper In this paper , the authors show that the loss landscape of a wide enough neural network has essentially a single basin. This leads to many permutations of the same model weights calculating the same function.

AI Researcher 130

AI Researcher AI Research Neural Network AI 130

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.

LLM

Bugra Akyildiz

NOVEMBER 13, 2022

Articles Pinterest wrote a very good/lengthy post on how they are incorporating short-term interest and real-time user actions. Some of the use cases that they are going after: Model pinners’ short-term interest : PinnerSAGE is trained using thousands of user actions over a long term, so it mostly captures long-term interest. On the other hand, realtime user action sequence models short-term user interest and is complementary to PinnerSAGE embedding.

Metadata 52

Metadata Computer Vision ML Machine Learning 52

Google Research AI blog

NOVEMBER 18, 2022

Posted by Mohammad Saleh, Software Engineer, Google Research, Brain Team, and Yinan Wang, Software Engineer, Google Workspace Information overload is a significant challenge for many organizations and individuals today. It can be overwhelming to keep up with incoming chat messages and documents that arrive at our inbox everyday. This has been exacerbated by the increase in virtual work and remains a challenge as many teams transition to a hybrid work environment with a mix of those working both

Software Engineer 52

Software Engineer Neural Network Natural Language Processing Machine Learning 52

Analytics Vidhya

NOVEMBER 18, 2022

This article was published as a part of the Data Science Blogathon. Deep Learning Overview Deep Learning is a subset of Machine Learning. Deep Learning is established on Artificial Neural Networks to mimic the human brain. In deep learning, we add several hidden layers to gather the most minute details to learn the data for […]. The post Analyzing and Comparing Deep Learning Models appeared first on Analytics Vidhya.

Deep Learning 390

Deep Learning Neural Network Machine Learning Data Science 390

DataRobot Blog

NOVEMBER 17, 2022

What’s your AI risk mitigation plan? Just as you wouldn’t set off on a journey without checking the roads, knowing your route, and preparing for possible delays or mishaps, you need a model risk management plan in place for your machine learning projects. A well-designed model combined with proper AI governance can help minimize unintended outcomes like AI bias.

Continuous Learning 52

Continuous Learning Explainability Explainable AI Machine Learning 52

Advertisement

Learn how to optimize email deliverability and drive greater email ROI. What lands your email in the customer’s inbox? Understanding those factors, otherwise known as email deliverability, is critical to getting the most return on your campaign investments. But the “rules” around which factors land you in the spam folder aren’t always easy to keep up with.

Analytics Vidhya

NOVEMBER 17, 2022

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction Competitive Deep Learning models rely on a wealth of training data, computing resources, and time. However, there are many tasks for which we don’t have enough labeled data at our disposal. Moreover, the need for running deep learning models on […].

Deep Learning 389

Deep Learning Data Science NLP 389

Analytics Vidhya

NOVEMBER 14, 2022

This article was published as a part of the Data Science Blogathon. Introduction Until now, we have seen two different approaches to state space search. i.e., Uninformed Search and Informed Search Strategies. These search strategies compute the path to the goal state from the initial state. A* Search Strategy is one of the best strategies […].

Algorithm 384

Algorithm Data Science 384

Analytics Vidhya

NOVEMBER 12, 2022

This article was published as a part of the Data Science Blogathon. Source: totaljobs.com Introduction TensorFlow is one of the most well-liked and promising deep learning frameworks for devising novel deep learning solutions. Given its popularity and wide usage in companies, startups, and business firms to automate things and develop new systems, it is imperative to have […].

Deep Learning 371

Deep Learning Data Science Automation Python 371

Analytics Vidhya

NOVEMBER 16, 2022

This article was published as a part of the Data Science Blogathon. Source: totaljobs.com Introduction Transformers have become a powerful tool for different natural language processing tasks. The impressive performance of the transformer is mainly attributed to its self-attention mechanism. However, training big Transformers with long sequences is impossible in most cases due to their quadratic […].

Natural Language Processing 305

Natural Language Processing Data Science BERT NLP 305

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.

Analytics Vidhya

NOVEMBER 16, 2022

This article was published as a part of the Data Science Blogathon. Source: [link] Introduction Nowadays, a lot of data is being generated and consumed, resulting in a huge amount of internet traffic exponentially across the globe. So it is very important to manage the traffic and serve users or customers better and more efficiently. […]. The post AWS Route 53 – The Efficient DNS Solution appeared first on Analytics Vidhya.

Data Science 291

Data Science 291

Analytics Vidhya

NOVEMBER 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction We all know that Data Cleaning and Preprocessing take up the most time in a Data Science project. While executing various pre-processing approaches, we may find several issues that can primarily be solved by a single library – Pandas. Pandas is a […]. The post Essential Pandas Operations You Must Bookmark Right Away appeared first on Analytics Vidhya.

Data Science 314

Data Science Python Machine Learning 314