ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. NLTK is appreciated for its broader nature, as it’s able to pull the right algorithm for any job.

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AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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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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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.

Machine Learning 52

Machine Learning Machine Learning Data Science Data Scientist 52

PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision. Also, you might want to check out our computer vision for deep learning program before you go.

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Machine Learning Machine Learning Deep Learning Deep Learning 56

Heartbeat

AUGUST 23, 2023

But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. But what if there was a way to unravel this language puzzle swiftly and accurately?

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Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. What is required to build an AI system?

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Pickl AI

NOVEMBER 8, 2023

Model Selection Picking the Right Algorithm Scikit-Learn boasts a variety of Machine Learning algorithms. The cheat sheet helps you select the right one for your specific task, be it regression, classification, or clustering. Is Scikit-Learn suitable for deep learning?

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Machine Learning Machine Learning Data Science Python 52

The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing. positive, negative, neutral). Words like “Descent”, “Average”, etc.

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AWS Machine Learning Blog

FEBRUARY 12, 2024

Sharing in-house resources with other internal teams, the Ranking team machine learning (ML) scientists often encountered long wait times to access resources for model training and experimentation – challenging their ability to rapidly experiment and innovate. If it shows online improvement, it can be deployed to all the users.

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Mlearning.ai

JUNE 23, 2023

Options (Free vs Paid) Closing Introduction In today’s increasingly globalized world, the ability to communicate in multiple languages has become a highly valuable skill. Language Models (LLMs) have revolutionized the field of natural language processing, bringing unprecedented advancements in understanding and generating human-like text.

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Database ML ML Natural Language Processing 52

Dataconomy

MAY 25, 2023

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? Explain how you would implement transfer learning in a deep learning model.

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AWS Machine Learning Blog

AUGUST 14, 2023

Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions. The BloomZ 176B model, one of the largest publicly available models, is a state-of-the-art instruction-tuned model that can perform various in-context few-shot learning and zero-shot learning NLP tasks.

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AWS Machine Learning Blog

MAY 25, 2023

This will create all the necessary infrastructure resources needed for this solution: SageMaker endpoints for the LLMs OpenSearch Service cluster API Gateway Lambda function SageMaker Notebook IAM roles Run the data_ingestion_to_vectordb.ipynb notebook in the SageMaker notebook to ingest data from SageMaker docs into an OpenSearch Service index.

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IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. Machine learning is a subset of AI. This blog post will clarify some of the ambiguity.

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The MLOps Blog

APRIL 5, 2023

In this comprehensive guide, we’ll explore the key concepts, challenges, and best practices for ML model packaging, including the different types of packaging formats, techniques, and frameworks. So, let’s dive in and discover everything you need to know about model packaging in machine learning.

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AWS Machine Learning Blog

APRIL 1, 2024

Machine learning (ML) research has proven that large language models (LLMs) trained with significantly large datasets result in better model quality. Distributed model training requires a cluster of worker nodes that can scale.

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AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. JumpStart provides many pre-trained language models called foundation models that can help you perform tasks such as article summarization, question answering, and conversation generation and image generation.

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ODSC - Open Data Science

JANUARY 29, 2024

Knowledge in these areas enables prompt engineers to understand the mechanics of language models and how to apply them effectively. These outputs, stored in vector databases like Weaviate, allow Prompt Enginers to directly access these embeddings for tasks like semantic search, similarity analysis, or clustering.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

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AWS Machine Learning Blog

MAY 1, 2024

AWS Trainium instances for training workloads SageMaker ml.trn1 and ml.trn1n instances, powered by Trainium accelerators, are purpose-built for high-performance deep learning training and offer up to 50% cost-to-train savings over comparable training optimized Amazon Elastic Compute Cloud (Amazon EC2) instances.

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IBM Journey to AI blog

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.

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AWS Machine Learning Blog

JANUARY 17, 2023

Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. Amazon SageMaker JumpStart provides one-click, end-to-end solutions for many common ML use cases. Fraud detection.

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Heartbeat

DECEMBER 5, 2023

Third-generation Tensor Cores have accelerated AI tasks, leading to breakthroughs in image recognition, natural language processing, and speech recognition. The H100 pioneered AI computing with its capability of machine learning and deep learning workloads. It offers single-precision performance up to 10.6

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AWS Machine Learning Blog

APRIL 25, 2024

We provide a comprehensive guide on how to deploy speaker segmentation and clustering solutions using SageMaker on the AWS Cloud. The added benefit of asynchronous inference is the cost savings by auto scaling the instance count to zero when there are no requests to process.

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AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. Why do we need an embeddings model? Nitin Eusebius is a Sr.

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AWS Machine Learning Blog

MAY 8, 2023

SageMaker provides single model endpoints (SMEs), which allow you to deploy a single ML model, or multi-model endpoints (MMEs), which allow you to specify multiple models to host behind a logical endpoint for higher resource utilization. TensorRT is an SDK developed by NVIDIA that provides a high-performance deep learning inference library.

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AWS Machine Learning Blog

OCTOBER 23, 2023

Given this mission, Talent.com and AWS joined forces to create a job recommendation engine using state-of-the-art natural language processing (NLP) and deep learning model training techniques with Amazon SageMaker to provide an unrivaled experience for job seekers. The recommendation system has driven an 8.6%

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Pickl AI

JULY 17, 2023

Unsupervised Learning Algorithms Unsupervised Learning Algorithms tend to perform more complex processing tasks in comparison to supervised learning. However, unsupervised learning can be highly unpredictable compared to natural learning methods. It can be either agglomerative or divisive.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. Give this technique a try to take your team’s ML modelling to the next level.

Data Science 130

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AWS Machine Learning Blog

MARCH 2, 2023

Hyperparameter optimization is highly computationally demanding for deep learning models. In our solution, we implement a hyperparameter grid search on an EKS cluster for tuning a bert-base-cased model for classifying positive or negative sentiment for stock market data headlines. to launch the cluster. eks-create.sh

Clustering 75

Clustering AWS Deep Learning Deep Learning 75

Snorkel AI

MAY 10, 2023

I’m a data scientist at Capital One on the EP2ML (enterprise product and platforms) team where I’m focusing on the natural language understanding and natural language processing (NLUNOP) capabilities of our virtual assistant Eno, or chatbot. Learn more, live! into the embedding space.

Data Science 52

Data Science Data Scientist AI AI 52

Snorkel AI

MAY 10, 2023

I’m a data scientist at Capital One on the EP2ML (enterprise product and platforms) team where I’m focusing on the natural language understanding and natural language processing (NLUNOP) capabilities of our virtual assistant Eno, or chatbot. Learn more, live! into the embedding space.

Data Science 52

Data Science Data Scientist AI AI 52

The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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