Towards AI

JULY 17, 2023

Last Updated on July 18, 2023 by Editorial Team Author(s): Muttineni Sai Rohith Originally published on Towards AI. Pyspark MLlib | Classification using Pyspark ML In the previous sections, we discussed about RDD, Dataframes, and Pyspark concepts. In this article, we will discuss about Pyspark MLlib and Spark ML.

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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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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. 2023| New| NA|36895.00|36895|

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Pickl AI

JANUARY 23, 2023

It is not a good when dealing with RNN (Recurrent Neural Networks) Also See: 5 Machine Learning Algorithms That Every ML Engineer Should know Microsoft CNTK CNTK is a deep learning framework that was created by Microsoft Research. Theano Theano is one of the fastest and simplest ML libraries, and it was built on top of NumPy.

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AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. We pick the first week of December 2023 in this example. This way, our analysis is based on clear and reliable imagery.

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ODSC - Open Data Science

MARCH 27, 2023

Botnets Detection at Scale — Lesson Learned from Clustering Billions of Web Attacks into Botnets. ML Governance: A Lean Approach Ryan Dawson | Principal Data Engineer | Thoughtworks Meissane Chami | Senior ML Engineer | Thoughtworks During this session, you’ll discuss the day-to-day realities of ML Governance.

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Towards AI

MAY 3, 2023

Last Updated on May 9, 2023 by Editorial Team Author(s): Sriram Parthasarathy Originally published on Towards AI. This code can cover a diverse array of tasks, such as creating a KMeans cluster, in which users input their data and ask ChatGPT to generate the relevant code. This is where ML CoPilot enters the scene.

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Hacker News

OCTOBER 15, 2024

Over the course of 2023, we rapidly scaled up our training clusters from 1K, 2K, 4K, to eventually 16K GPUs to support our AI workloads. Today, we’re training our models on two 24K-GPU clusters. We don’t expect this upward trajectory for AI clusters to slow down any time soon. But things have rapidly accelerated.

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ODSC - Open Data Science

MAY 30, 2023

Be sure to check out his talk, “ ML Applications in Asset Allocation and Portfolio Management ,” there! In 2023-Q1, we even saw failing banks like SVB simply because of investments in “safe” treasury bonds. Editor’s note: Peter Schwendner, PhD is a speaker for ODSC Europe this June.

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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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AWS Machine Learning Blog

SEPTEMBER 26, 2024

However, building large distributed training clusters is a complex and time-intensive process that requires in-depth expertise. Amazon SageMaker HyperPod, introduced during re:Invent 2023, is a purpose-built infrastructure designed to address the challenges of large-scale training.

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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

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. Register for ODSC East 2023 now. You will find all of these sessions, and many, many more, at ODSC East 2023 on May 9th — 11th. Check out a few of them below.

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ODSC - Open Data Science

MAY 24, 2023

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions. Final ODSC Europe 2023 Schedule Released! Here’s why. Here’s what you can expect from ODSC Europe.

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ODSC - Open Data Science

JULY 22, 2023

We’re a few weeks removed from ODSC Europe 2023 and we couldn’t have left on a better note. Here are some highlights from ODSC Europe 2023, including some pictures of speakers and attendees, popular talks, and a summary of what kept people busy. That’s it for our ODSC Europe 2023 highlights! What’s next?

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ODSC - Open Data Science

APRIL 13, 2023

Botnets Detection at Scale — Lessons Learned From Clustering Billions of Web Attacks Into Botnets Read more to learn about the data flow, the challenges, and the way we get successful results of botnet detection. Top Data Science and AI News: March 2023 From Google’s Bard to GPT-4, March was a big month for data science and AI news.

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Google Research AI blog

JULY 23, 2023

Posted by Cat Armato, Program Manager, Google Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. We build ML systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more.

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ODSC - Open Data Science

JULY 14, 2023

Below you’ll find just a few of the many expert-led sessions at ODSC Europe 2023 that attendees loved — and you can view them for yourself here ! And don’t miss the chance to join us for our upcoming free virtual Generative AI Summit on July 20th and ODSC West 2023 in San Francisco (October 31st-November 3rd). What’s next?

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Towards AI

MAY 2, 2023

Last Updated on May 9, 2023 by Editorial Team Author(s): Sriram Parthasarathy Originally published on Towards AI. Use plain English to build ML models to identify profitable customer segments. Perform K-means clustering using income and spending variables, and present the breakdown of spending for each cluster.

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Dataconomy

MAY 16, 2023

Machine learning techniques: Familiarity with a wide range of machine learning algorithms and techniques allows data scientists to apply appropriate models for predictive analysis, clustering, classification, and recommendation systems.

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Snorkel AI

MARCH 30, 2023

Rapid, model-guided iteration with New Studio for all core ML tasks. Enhanced studio experience for all core ML tasks. Now you can import your own embedding directly into SF and once imported, the data can be visualized using the cluster view for an intuitive understanding of your custom embeddings. PDF extraction improvements.

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ODSC - Open Data Science

JUNE 7, 2023

Gözde Gül Şahin | Assistant Professor, KUIS AI Fellow | KOC University Fraud Detection with Machine Learning: Laura Mitchell | Senior Data Science Manager | MoonPay Deep Learning and Comparisons between Large Language Models: Hossam Amer, PhD | Applied Scientist | Microsoft Multimodal Video Representations and Their Extension to Visual Language Navigation: (..)

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Towards AI

JULY 22, 2023

Last Updated on July 24, 2023 by Editorial Team Author(s): Cristian Originally published on Towards AI. This is similar to how machine learning (ML) can seem at first. This way, it might end up clustering spam emails together, not because it knew they were spam, but because it found patterns. But don’t worry!

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Snorkel AI

SEPTEMBER 29, 2023

How you develop and use your proprietary data is the key to unlocking its value and to delivering accurate, reliable, and trustworthy AI and ML applications. ML researchers and practitioners at AI startups and large enterprises have relied on curating additional labeled data to achieve better performance on specific tasks.

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AWS Machine Learning Blog

JANUARY 17, 2024

We then discuss the various use cases and explore how you can use AWS services to clean the data, how machine learning (ML) can aid in this effort, and how you can make ethical use of the data in generating visuals and insights. The following reference architecture depicts a workflow using ML with geospatial data.

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Flipboard

FEBRUARY 16, 2023

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. As part of a single cluster run, you can spin up a cluster of Trn1 instances with Trainium accelerators. Trn1 UltraClusters can host up to 30,000 Trainium devices and deliver up to 6 exaflops of compute in a single cluster.

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AWS Machine Learning Blog

APRIL 29, 2024

Trainium is the second-generation machine learning (ML) accelerator that AWS purpose built to help developers access high-performance model training accelerators to help lower training costs by up to 50% over comparable Amazon Elastic Compute Cloud (Amazon EC2) instances. Our cluster consisted of 16 nodes, each equipped with a trn1n.32xlarge

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody. Everybody can train a model.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody. Everybody can train a model.

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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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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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Pickl AI

OCTOBER 24, 2024

Summary: This article compares Artificial Intelligence (AI) vs Machine Learning (ML), clarifying their definitions, applications, and key differences. While AI aims to replicate human intelligence across various domains, ML focuses on learning from data to improve performance. What is Machine Learning?

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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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AWS Machine Learning Blog

NOVEMBER 6, 2024

Amazon Transcribe is a machine learning (ML) based managed service that automatically converts speech to text, enabling developers to seamlessly integrate speech-to-text capabilities into their applications. Transcribe audio with Amazon Transcribe In this case, we use an AWS re:Invent 2023 technical talk as a sample.

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Becoming Human

MAY 15, 2023

Note : Now write some articles or blogs on the things you have learned because this thing will help you to develop soft skills as well if you want to publish some research paper on AI/ML so this writing habit will help you there for sure. It provides end-to-end pipeline components for building scalable and reliable ML production systems.

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ODSC - Open Data Science

OCTOBER 13, 2023

After that, he worked as a quant at a hedge fund on a 600 GPU cluster. After studying chemical engineering Jepson worked for Intel/Micron in applied semiconductor building process control and fault models. Taylor is a frequent speaker and writer on AI topics.

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ODSC - Open Data Science

MAY 2, 2023

The Universal Sentence Encoder (USE) is a sentence encoder built by Google that specializes in text classification, semantic similarity and clustering. We relied on Shopify’s ML platform to get the job done. Our ML platform is built upon Ray, which allowed us to scale easily. What is the Universal Sentence Encoder?

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