Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

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Dataconomy

MAY 2, 2023

The machine learning systems developed by Machine Learning Engineers are crucial components used across various big data jobs in the data processing pipeline. Additionally, Machine Learning Engineers are proficient in implementing AI or ML algorithms. Is ML engineering a stressful job?

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ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

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Data Science Dojo

OCTOBER 31, 2024

Growth Outlook: Companies like Google DeepMind, NASA’s Jet Propulsion Lab, and IBM Research actively seek research data scientists for their teams, with salaries typically ranging from $120,000 to $180,000. With the continuous growth in AI, demand for remote data science jobs is set to rise.

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Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. Power BI Wizard It is a popular business intelligence tool that empowers you to explore data.

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AWS Machine Learning Blog

FEBRUARY 7, 2024

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Under Labels – optional , for Labels , choose Create new labels.

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ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. At the end of this article, you will learn how to use Pytorch pretrained DenseNet 201 model to classify different animals into 48 distinct categories.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Data exploration and model development were conducted using well-known machine learning (ML) tools such as Jupyter or Apache Zeppelin notebooks. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. HBase is employed to offer real-time key-based access to data.

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Data Science AWS Hadoop Data Scientist 68

The MLOps Blog

JUNE 13, 2024

Data scientists often lack focus, time, or knowledge about software engineering principles. As a result, poor code quality and reliance on manual workflows are two of the main issues in ML development processes. You need to think about and improve the data, the model, and the code, which adds layers of complexity.

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ML ML Data Scientist Azure 59

Dataconomy

AUGUST 7, 2023

An AI database is not merely a repository of information but a dynamic and specialized system meticulously crafted to cater to the intricate demands of AI and ML applications. Herein lies the crux of the AI database’s significance: it is tailored to meet the intricate requirements that underpin the success of AI and ML endeavors.

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O'Reilly Media

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. What does a modern technology stack for streamlined ML processes look like? Why: Data Makes It Different. All ML projects are software projects.

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ML ML Data Scientist AWS 145

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

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Pickl AI

NOVEMBER 29, 2024

It enhances scalability, experimentation, and reproducibility, allowing ML teams to focus on innovation. This blog highlights the importance of organised, flexible configurations in ML workflows and introduces Hydra. Machine Learning projects evolve rapidly, frequently introducing new data , models, and hyperparameters.

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Machine Learning Machine Learning ML ML 52

Data Science Dojo

FEBRUARY 6, 2025

Here’s a complete guide to understanding all about LLMs What is Data Annotation? Data annotation is the process of labeling data to make it understandable and usable for machine learning (ML) models. Below are a few reasons that make data annotation a critical component for language models.

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AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker. This is a guest post written by Axfood AB.

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Machine Learning Machine Learning ML ML 131

Dataconomy

AUGUST 25, 2023

Performance metrics in machine learning can even be used at the early stages of ML model development such as model prediction ( Image credit ) Step 3: Model prediction The model prediction is the pinnacle of a machine learning journey, where the rubber meets the road and the model’s abilities are put to the test.

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Algorithm ML ML Machine Learning 91

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. Composable ML then lets you add new types of feature engineering or build entirely new models.

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ML ML Data Scientist Machine Learning 52

Iguazio

DECEMBER 18, 2023

For data science practitioners, productization is key, just like any other AI or ML technology. However, it's important to contextualize generative AI within the broader landscape of AI and ML technologies. By doing so, you can ensure quality and production-ready models. Here’s to a successful 2024!

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Machine Learning Machine Learning ML ML 134

DagsHub

AUGUST 29, 2024

Source: Author Introduction Machine learning (ML) models, like other software, are constantly changing and evolving. Version control systems (VCS) play a key role in this area by offering a structured method to track changes made to models and handle versions of data and code used in these ML projects.

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ODSC - Open Data Science

OCTOBER 21, 2024

Fortunately, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. But let’s first take a look at some of the tools for ML evaluation that are popular for responsible AI. It includes methods for addressing fairness issues by adjusting training data, models, or outputs.

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ML ML Machine Learning Machine Learning 52

AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

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ML ML AWS Machine Learning 112

Data Science Dojo

FEBRUARY 23, 2024

GPTs for Data science are the next step towards innovation in various data-related tasks. These are platforms that integrate the field of data analytics with artificial intelligence (AI) and machine learning (ML) solutions. Power BI Wizard It is a popular business intelligence tool that empowers you to explore data.

Data Science 195

Data Science Data Analysis Data Analysis Machine Learning 195

The MLOps Blog

OCTOBER 8, 2024

In the machine learning (ML) and artificial intelligence (AI) domain, managing, tracking, and visualizing model training processes is a significant challenge due to the scale and complexity of managed data, models, and resources.

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ML ML Machine Learning Machine Learning 52

phData

AUGUST 24, 2023

What Does a Credit Score or Decisioning ML Pipeline Look Like? Now that we have a firm grasp on the underlying business case, we will now define a machine learning pipeline in the context of credit models. Feature selection is crucial as it directly impacts the model’s performance. loan default or not). Want to learn more?

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ML ML Machine Learning Machine Learning 52

Data Science Dojo

FEBRUARY 23, 2024

Power BI Wizard It is a popular business intelligence tool that empowers you to explore data. The data exploration allows you to create reports, use DAX formulas for data manipulation, and suggest best practices for data modeling. The learning assistance provides deeper insights and improved accuracy.

Data Science 195

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Smart Data Collective

DECEMBER 19, 2021

For example, the Impute library package handles the imputation of missing values, MinMaxScaler scales datasets, or uses Autumunge to prepare table data for machine learning algorithms. Besides, Python allows creating data models, systematizing data sets, and developing web services for proficient data processing.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

The IDP Well-Architected Custom Lens follows the AWS Well-Architected Framework, reviewing the solution with six pillars with the granularity of a specific AI or machine learning (ML) use case, and providing the guidance to tackle common challenges. Model monitoring The performance of ML models is monitored for degradation over time.

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AWS Machine Learning Blog

APRIL 29, 2024

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. Metaflow’s coherent APIs simplify the process of building real-world ML/AI systems in teams.

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AWS ML ML Python 118

Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. Data forecasting has come a long way since formidable data processing-boosting technologies such as machine learning were introduced.

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Machine Learning Machine Learning ML ML 52

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. How do I develop my body of work?

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ML ML Data Scientist Machine Learning 52

AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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AWS Data Science ML ML 129

Iguazio

DECEMBER 18, 2023

For data science practitioners, productization is key, just like any other AI or ML technology. However, it's important to contextualize generative AI within the broader landscape of AI and ML technologies. By doing so, you can ensure quality and production-ready models. Here’s to a successful 2024!

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ML ML AI AI 52

phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

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AWS Machine Learning Blog

JUNE 22, 2023

Utilizing data streamed through LnW Connect, L&W aims to create better gaming experience for their end-users as well as bring more value to their casino customers. Predictive maintenance is a common ML use case for businesses with physical equipment or machinery assets. We used AutoGluon to explore several classic ML algorithms.

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The MLOps Blog

NOVEMBER 30, 2022

Data science teams currently struggle with managing multiple experiments and models and need an efficient way to store, retrieve, and utilize details like model versions, hyperparameters, and performance metrics. ML model versioning: where are we at? The short answer is we are in the middle of a data revolution.

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ML ML Machine Learning Machine Learning 52

AWS Machine Learning Blog

APRIL 25, 2024

Hugging Face is a popular open source hub for machine learning (ML) models. He has helped launch and scale the AI/ML powered Amazon SageMaker service and has implemented several proofs of concept using Amazon AI services. client("s3") o = urlparse(s3_file, allow_fragments=False) bucket = o.netloc key = o.path.lstrip("/") s3.download_file(bucket,

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