Hacker News

JUNE 12, 2024

Solving this problem requires a robust and high-speed network infrastructure as well as efficient data transfer protocols and algorithms. This includes developing new algorithms and techniques for efficient large-scale training and integrating new software tools and frameworks into our infrastructure.

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Data Science Dojo

JUNE 20, 2023

The game-changing technological marvels have got everyone talking and has to be topping the charts in 2023. A large language model, referred to as an LLM, is an advanced machine learning algorithm capable of identifying, condensing, translating, predicting, and generating various forms of text and content using extensive datasets.

Natural Language Processing 195

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ODSC - Open Data Science

MARCH 15, 2023

We’re excited to announce some of the incredible and totally new sessions we have coming to ODSC East May 9th — 11th, 2023 in Boston and online. You’ll also explore centrality metrics, networking density, various layout algorithms, and strategies for interpreting and communicating graph data. Register for ODSC East 2023 now.

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Dataconomy

SEPTEMBER 22, 2023

Intelligent data classification Intelligent data classification is a process where artificial intelligence (AI) algorithms are used to automatically categorize and classify data based on its content, relevance, and importance; getting data ready for archiving. There are several ways to use AI for data archiving.

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NYU Center for Data Science

JANUARY 25, 2024

2023’s event, held in New Orleans in December, was no exception, showcasing groundbreaking research from around the globe. In the world of data science, few events garner as much attention and excitement as the annual Neural Information Processing Systems (NeurIPS) conference.

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AWS Machine Learning Blog

SEPTEMBER 26, 2024

During the iterative research and development phase, data scientists and researchers need to run multiple experiments with different versions of algorithms and scale to larger models. However, building large distributed training clusters is a complex and time-intensive process that requires in-depth expertise.

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Towards AI

SEPTEMBER 10, 2023

Last Updated on September 11, 2023 by Editorial Team Author(s): Magdalena Kortas Originally published on Towards AI. As the El Niño phenomenon approaches in the summer of 2023, there is a dual concern of record-breaking warmth and extreme aridity. You can also read this article on Kablamo Engineering Blog.

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Google Research AI blog

APRIL 30, 2023

Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels.

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ODSC - Open Data Science

OCTOBER 18, 2023

To find out, we’ve taken some of the upcoming tutorials and workshops from ODSC West 2023 and let the experts via their topics guide us toward building better machine learning. The process begins with a careful observation of customer data and an assessment of whether there are naturally formed clusters in the data.

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Machine Learning Machine Learning Clustering Data Science 52

ODSC - Open Data Science

MARCH 27, 2023

Botnets Detection at Scale — Lesson Learned from Clustering Billions of Web Attacks into Botnets. In this session, you will learn how explainability can help you identify poor model performance or bias, as well as discuss the most commonly used algorithms, how they work, and how to get started using them.

Machine Learning 98

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Google Research AI blog

JULY 23, 2023

We build ML systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more. Google is proud to be a Diamond Sponsor of the 40th International Conference on Machine Learning (ICML 2023), a premier annual conference, which is being held this week in Honolulu, Hawaii.

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Machine Learning Machine Learning ML ML 77

The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.

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ODSC - Open Data Science

FEBRUARY 17, 2023

NLP Skills for 2023 These skills are platform agnostic, meaning that employers are looking for specific skillsets, expertise, and workflows. TensorFlow is desired for its flexibility for ML and neural networks, PyTorch for its ease of use and innate design for NLP, and scikit-learn for classification and clustering.

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Data Science Dojo

FEBRUARY 3, 2023

Computer vision with Python and OpenCV Computer vision is a field of artificial intelligence that focuses on the development of algorithms and models that can interpret and understand visual information. One project idea in this area could be to build a facial recognition system using Python and OpenCV.

Data Science 195

Data Science Python Machine Learning Machine Learning 195

Towards AI

APRIL 5, 2023

Last Updated on April 6, 2023 by Editorial Team Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. The articles cover a range of topics, from the basics of Rust to more advanced machine learning concepts, and provide practical examples to help readers get started with implementing ML algorithms in Rust.

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Towards AI

APRIL 14, 2023

Last Updated on April 17, 2023 by Editorial Team Author(s): Kevin Berlemont, PhD Originally published on Towards AI. In the second part, I will present and explain the four main categories of XML algorithms along with some of their limitations. Thus tail labels have an inflated score in the metric.

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Data Science Dojo

JULY 2, 2024

Adaptive AI has risen as a transformational technological concept over the years, leading Gartner to name it as a top strategic tech trend for 2023. Unlike traditional AI, which follows set rules and algorithms and tends to fall apart when faced with obstacles, adaptive AI systems can modify their behavior based on their experiences.

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Towards AI

JUNE 27, 2023

Last Updated on June 27, 2023 by Editorial Team Source: Unsplash This piece dives into the top machine learning developer tools being used by developers — start building! With an impressive collection of efficient tools and a user-friendly interface, it is ideal for tackling complex classification, regression, and cluster-based problems.

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Machine Learning Machine Learning ML ML 93

Dataconomy

JUNE 29, 2023

Python machine learning packages have emerged as the go-to choice for implementing and working with machine learning algorithms. The field of machine learning, known for its algorithmic complexity, has undergone a significant transformation in recent years. Why do you need Python machine learning packages?

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Pickl AI

JANUARY 23, 2023

People don’t even need the in-depth knowledge of the various machine learning algorithms as it contains pre-built libraries. PyTorch PyTorch is a popular, open-source, and lightweight machine learning and deep learning framework built on the Lua-based scientific computing framework for machine learning and deep learning algorithms.

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Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

AUGUST 15, 2023

You’ll get hands-on practice with unsupervised learning techniques, such as K-Means clustering, and classification algorithms like decision trees and random forest. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark.

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NYU Center for Data Science

NOVEMBER 15, 2023

We’re excited to announce that many CDS faculty, researchers, and students will present at the upcoming thirty-seventh 2023 NeurIPS (Neural Information Processing Systems) Conference , taking place Sunday, December 10 through Saturday, December 16. The conference will take place in-person at the New Orleans Ernest N.

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Towards AI

JULY 17, 2023

Last Updated on July 18, 2023 by Editorial Team Author(s): Muttineni Sai Rohith Originally published on Towards AI. Later on, we will train a classifier for Car Evaluation data, by Encoding the data, Feature extraction and Developing classifier model using various algorithms and evaluate the results.

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ML ML Decision Trees Machine Learning 85

Explosion

NOVEMBER 28, 2023

Throughout 2023, we have introduced support for Large Language Models (LLMs) through spacy-llm, added customizable task routing, expanded our QA features with inter-annotator agreement metrics, infused more interactivity into the UI, and shared several open-source Prodigy plug-ins with the community. are our biggest in almost two years.

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Python Algorithm Clustering Machine Learning 78

Becoming Human

MAY 15, 2023

The two most common types of supervised learning are classification , where the algorithm predicts a categorical label, and regression , where the algorithm predicts a numerical value. Unsupervised Learning In this type of learning, the algorithm is trained on an unlabeled dataset, where no correct output is provided.

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Data Science Machine Learning Machine Learning Database 75

Flipboard

APRIL 4, 2023

The crux of the clash was whether Google’s AI solution to one of chip design’s thornier problems was really better than humans or state-of-the-art algorithms. In Circuit Training and Morpheus, a separate algorithm fills in the gaps with the smaller parts, called standard cells. The agent places one block at a time on the chip canvas.

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ODSC - Open Data Science

OCTOBER 13, 2023

At Google, it was his responsibility to maintain and improve the quality of our core web search algorithms during a time of twenty-fold growth. After that, he worked as a quant at a hedge fund on a 600 GPU cluster. Taylor is a frequent speaker and writer on AI topics.

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Snorkel AI

SEPTEMBER 29, 2023

Some machine learning algorithms, such as clustering and self-supervised learning , do not require data labels, but their direct business applications are limited. By combining signals and learning where they agree and disagree, the weak supervision algorithm learns when, where, and how much to trust each one.

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Machine Learning Machine Learning Data Science ML 59

Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. Use machine learning algorithms to build a fraud detection model and identify potentially fraudulent transactions.

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Towards AI

OCTOBER 31, 2024

Hype Cycle for Emerging Technologies 2023 (source: Gartner) Despite AI’s potential, the quality of input data remains crucial. Algorithms can automatically clean and preprocess data using techniques like outlier and anomaly detection. GenAI can now assist in direct data mapping and cleaning by identifying and fixing inconsistencies.

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Data Quality Analytics Analytics Clean Data 103

PyImageSearch

JUNE 19, 2023

Each service uses unique techniques and algorithms to analyze user data and provide recommendations that keep us returning for more. By analyzing how users have interacted with items in the past, we can use algorithms to approximate the utility function and make personalized recommendations that users will love.

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K-nearest Neighbors Clustering Algorithm Deep Learning 56

AWS Machine Learning Blog

NOVEMBER 7, 2024

Markdown pricing is a pricing approach that adjusts prices over time and is a common strategy to maximize revenue from goods that have a limited lifespan or are subject to seasonal demand (Sul 2023). The markdown pricing algorithmic solution Zalando relies on is a forecast-then-optimize approach (Kunz et al. 2023 and Streeck et al.

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Mlearning.ai

JUNE 6, 2023

HOGs are great feature detectors and can also be used for object detection with SVM but due to many other State of the Art object detection algorithms like YOLO, SSD, present out there, we don’t use HOGs much for object detection. This is a simple but very interesting project due to its prediction power. This is a simple project.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52

ODSC - Open Data Science

SEPTEMBER 20, 2024

However, building and deploying these algorithms follows a few consistent steps. As such, K-means clustering is a solid choice and easy to implement. However, more complex algorithms may be necessary to reduce false positives, given the sensitivity of the application. Still, the long-term benefits are often worth it.

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AI AI Machine Learning Machine Learning 40

Towards AI

MARCH 26, 2024

However, whether OpenAI/Microsoft Azure has the capacity for a 50,000 or 150,000 GPU single training cluster remains unclear. Similarly, Google accelerated the deployment of TPUv5 chips (designed in partnership with Broadcom) in late 2023, and its Gemini 2.0 GPT-5 will likely be trained on H100s with roughly 3x more compute per GPU.

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AI AI Clustering Azure 79

Pickl AI

SEPTEMBER 3, 2023

In 2023, the expected reach of the AI market is supposed to reach the $500 billion mark and in 2030 it is supposed to reach $1,597.1 The specific techniques and algorithms used can vary based on the nature of the data and the problem at hand. This algorithm is efficient and effective for high-dimensional datasets.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

NYU Center for Data Science

SEPTEMBER 13, 2024

The world of multi-view self-supervised learning (SSL) can be loosely grouped into four families of methods: contrastive learning, clustering, distillation/momentum, and redundancy reduction. I don’t think it will replace existing algorithms,” Shwartz-Ziv noted.

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