Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy.

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How to Learn Machine Learning

MAY 14, 2023

Acquiring Essential Machine Learning Knowledge Once you have a strong foundation in mathematics and programming, it’s time to dive into the world of machine learning. Additionally, you should familiarize yourself with essential machine learning concepts such as feature engineering, model evaluation, and hyperparameter tuning.

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Becoming Human

MAY 9, 2024

Artificial intelligence, machine learning, natural language processing, and other related technologies are paving the way for a smarter “everything.” As a result, we can automate manual processes, improve risk management, comply with regulations, and maintain data consistency.

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IBM Journey to AI blog

JUNE 14, 2023

With a foundation model, often using a kind of neural network called a “transformer” and leveraging a technique called self-supervised learning, you can create pre-trained models for a vast amount of unlabeled data. This is usually text, but it can also be code, IT events, time series, geospatial data, or even molecules.

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Data Science 101

OCTOBER 31, 2019

The former is a term used for models where the data has been labeled, whereas, unsupervised learning, on the other hand, refers to unlabeled data. Classification is a form of supervised learning technique where a known structure is generalized for distinguishing instances in new data. Classification. Regression.

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Becoming Human

MARCH 16, 2023

Like in the human brain, these neurons work together to process information and make predictions or decisions. The more layers of interconnected neurons a neural network has, the more “deep” it is.

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ODSC - Open Data Science

NOVEMBER 8, 2023

One common approach is to use supervised learning. The LLM learns to map the input to the output by minimizing a loss function. Natural Language Processing Last but certainly not least, you need to know quite a bit about natural language processing, aka NLP.

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Pickl AI

SEPTEMBER 3, 2024

The Importance of Data Annotation It is essential in the realm of Artificial Intelligence and Machine Learning. It lays the groundwork for training models, ensuring accuracy, and facilitating supervised learning. By providing context and structure, annotated data enables machines to learn effectively and make informed decisions.

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How to Learn Machine Learning

SEPTEMBER 6, 2024

AI for cybersecurity leverages AI ML services to assess and correlate events and security threats across multiple sources and turn them into actionable insights that the security team uses for further assessment, response, and reporting. However, many of these events are not harmful, yet missing some cyber threats can be enormous.

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ODSC - Open Data Science

JULY 12, 2024

The fields of AI and data science are changing rapidly and ODSC West 2024 is evolving to ensure we keep you at the forefront of the industry with our all-new tracks, AI Agents , What’s Next in AI, and AI in Robotics , and our updated tracks NLP, NLU, and NLG , and Multimodal and Deep Learning , and LLMs and RAG.

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Heartbeat

MARCH 7, 2024

ScikitLLM is interesting because it seamlessly integrates LLMs into your traditional Scikit-learn (Sklearn) library. This means Scikit-LLM brings the power of powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.

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Heartbeat

OCTOBER 11, 2023

Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach. This is why the technique is known as "deep" learning. This is due to their capacity to adapt to new circumstances and learn from data.

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ODSC - Open Data Science

APRIL 26, 2023

It does this by analyzing adverse event reports and identifying potential safety issues associated with specific medications or medical devices. This aids researchers and medical professionals to better understand regulations to maintain compliance while being able to focus greater resources on medical research.

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Heartbeat

FEBRUARY 7, 2023

image by rawpixel.com Understanding the concept of language models in natural language processing (NLP) is very important to anyone working in the Deep learning and machine learning space.

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Heartbeat

JULY 6, 2023

At a high level, the Swin Transformer is based on the transformer architecture, which was originally developed for natural language processing but has since been adapted for computer vision tasks. The Swin Transformer is part of a larger trend in deep learning towards attention-based models and self-supervised learning.

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Heartbeat

FEBRUARY 15, 2023

Source: [link] Text classification is an interesting application of natural language processing. It is a supervised learning methodology that predicts if a piece of text belongs to one category or the other. These algorithms can perform sentiment analysis, create spam filters, and other applications.

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ODSC - Open Data Science

OCTOBER 15, 2023

Ikigai Labs Ikigai Labs is a company that provides a platform for building and managing natural language processing models. Active learning is a type of machine learning that involves iteratively querying a human for labels for data points that are most informative for the model.

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Kaggle

JULY 29, 2020

I also have experience in building large-scale distributed text search and Natural Language Processing (NLP) systems. NeuML was working on a real-time sports event tracking application, neuspo but sports along with everything else was being shut down and there were no sports to track.

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Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. Semi-Supervised Learning : Training is done using both labeled and unlabeled data.

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Pickl AI

SEPTEMBER 12, 2024

Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.

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Heartbeat

FEBRUARY 8, 2024

Cross-modal retrieval is a branch of computer vision and natural language processing that links visual and verbal descriptions. Photo in pexel.com With technological advancements, many multimedia data requests efficient ways to search for and obtain information across several methodologies.

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. During the training process, the model accepts sequences of words with one or more words missing. The model then predicts the missing words (see “what is self-supervised learning?”

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. During the training process, the model accepts sequences of words with one or more words missing. The model then predicts the missing words (see “what is self-supervised learning?”

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Snorkel AI

JANUARY 16, 2024

As humans, we learn a lot of general stuff through self-supervised learning by just experiencing the world. Natural language processing itself shouldn’t just focus on text. More Snorkel AI events coming! Snorkel has more live online events coming. I think this trend is starting right now.

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Heartbeat

FEBRUARY 28, 2023

U-Net , U-Net++ ], whereas unsupervised learning eliminates this requirement [see this r eview paper ]. Semi-supervised learning lies in between supervised and unsupervised learning, which we will learn in detail in the following sections. What is Semi-supervised Learning (SSL)?

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phData

OCTOBER 21, 2024

What Are Large Language Models? Large Language Models are deep learning models that recognize, comprehend, and generate text, performing various other natural language processing (NLP) tasks. At its core, machine learning is about finding and learning patterns in data that can be used to make decisions.

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Heartbeat

NOVEMBER 16, 2023

An In-depth Look into Evaluating AI Outputs, Custom Criteria, and the Integration of Constitutional Principles Photo by Markus Winkler on Unsplash Introduction In the age of conversational AI, chatbots, and advanced natural language processing, the need for systematic evaluation of language models has never been more pronounced.

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Google Research AI blog

NOVEMBER 28, 2022

Posted by Cat Armato, Program Manager, Google This week marks the beginning of the 36th annual Conference on Neural Information Processing Systems ( NeurIPS 2022 ), the biggest machine learning conference of the year. Arik , Deniz Yuret, Alper T.

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The MLOps Blog

MARCH 21, 2023

The service will consume the features in real time, generate predictions in near real-time , such as in an event processing pipeline, and write the outputs to a prediction queue. You can read this article to learn how to choose a data labeling tool. Offline batch inference The client updates features in the feature store.

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