LevelAI

MARCH 23, 2023

According to one of our Level AI senior machine learning (ML) engineers interviewed for this blog, the answer is a clear yes– because knowing customer intent enables business stakeholders to get a holistic view, and then make rapid business or technical decisions based on the information. Get a free demo today!

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Pickl AI

APRIL 5, 2023

Measuring Performance Model Performance Bias-Variance Visualisation Feature Engg Demo Feature Scaling Introduction to Machine Learning with R by Simplilearn This is a new introduction to the Machine Learning domain, but the course has received accolades from the learners. What Are The Job Responsibilities of an ML Engineer?

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AWS Machine Learning Blog

MAY 13, 2024

His expertise is in reproducible and end-to-end AI/ML methods, practical implementations, and helping global healthcare customers formulate and develop scalable solutions to interdisciplinary problems. He has two graduate degrees in physics and a doctorate in engineering.

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The MLOps Blog

NOVEMBER 14, 2023

Visualizing deep learning models can help us with several different objectives: Interpretability and explainability: The performance of deep learning models is, at times, staggering, even for seasoned data scientists and ML engineers. Data scientists and ML engineers: Creating and training deep learning models is no easy feat.

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The MLOps Blog

SEPTEMBER 7, 2023

This situation is not different in the ML world. Data Scientists and ML Engineers typically write lots and lots of code. Cost to refactor, performance, reusability, legibility, or, more simply put, technical debt can hinder a company’s capacity to grow in a sustainable way.

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AWS Machine Learning Blog

APRIL 11, 2023

Note that these passwords have been configured for demo purposes. For this demo, we have set up a simulated on-premises environment with a bastion host and a Windows application. region For this demo, we use a simulated Windows on-premises application. He helps customers migrate big data and AL/ML workloads to AWS.

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Chatbots Life

MAY 12, 2023

We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers? Will ChatGPT replace ML Engineers? Will ChatGPT replace ML Engineers? We will answer the question “ Will you lose your job?” And, as mentioned before.

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DataRobot Blog

SEPTEMBER 13, 2022

Companies at this stage will likely have a team of ML engineers dedicated to creating data pipelines, versioning data, and maintaining operations monitoring data, models & deployments. Request a demo. Groups across the enterprise, including process and application design, understand the value of data.

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Snorkel AI

OCTOBER 27, 2023

How to fine-tune and customize LLMs Hoang Tran, ML Engineer at Snorkel AI, outlined how he saw LLMs creating value in enterprise environments. Book a demo today. The conversation included notes about how much time data scientists spend preparing data, and the responsibility that comes with using AI.

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AWS Machine Learning Blog

JUNE 3, 2024

This instance configuration is sufficient for the demo. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice. Ryan Gomes is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice. For Deployment name , enter a name.

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Mlearning.ai

AUGUST 18, 2023

As an ML engineer you’re in charge of some code/model. Also same expertise rule applies for an ML engineer, the more versed you are in MLOps the better you can foresee issues, fix data/model bugs and be a valued team member. Running invoke from cmd: $ inv download-best-model We’re decoupling MLOps from actual ML code.

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DevOps Python ML ML Engineer 52

Snorkel AI

OCTOBER 27, 2023

How to fine-tune and customize LLMs Hoang Tran, ML Engineer at Snorkel AI, outlined how he saw LLMs creating value in enterprise environments. Book a demo today. The conversation included notes about how much time data scientists spend preparing data, and the responsibility that comes with using AI.

LLM 59

LLM Data Scientist Machine Learning Large Language Models 59

Snorkel AI

MAY 26, 2023

So we’ll learn a little bit about that, and then we’ll discuss an example of how you can leverage Scikit-Learn within Snowflake and Snowpark to implement some of these feature engineering techniques and also do machine learning model training and inference. The demo is actually very simple.

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ML Python Machine Learning Data Scientist 52

Snorkel AI

MAY 26, 2023

So we’ll learn a little bit about that, and then we’ll discuss an example of how you can leverage Scikit-Learn within Snowflake and Snowpark to implement some of these feature engineering techniques and also do machine learning model training and inference. The demo is actually very simple.

ML 52

ML Python Machine Learning Data Scientist 52

Snorkel AI

OCTOBER 27, 2023

How to fine-tune and customize LLMs Hoang Tran, ML Engineer at Snorkel AI, outlined how he saw LLMs creating value in enterprise environments. Our Snorkel Custom program puts our world-class engineers and researchers to work on your most promising challenges to deliver data sets or fully-built LLM or generative AI applications, fast.

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LLM Data Scientist Machine Learning Large Language Models 52

ODSC - Open Data Science

JANUARY 3, 2025

Finally, Week 4 ties it all together, guiding participants through the practical builder demos from cloning compound AI architectures to building production-ready applications. Cloning NotebookLM with Open Weights Models Niels Bantilan, Chief ML Engineer atUnion.AI

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Bugra Akyildiz

MAY 14, 2023

They demonstrate how this platform enables a better model evaluation experience through interactive characterization and visualization of ML model performance and interactive data augmentation and comparison. They have released the Visual Blocks for ML framework, along with a demo and Colab examples.

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The MLOps Blog

MARCH 28, 2023

MLOps maturity levels at Brainly MLOps level 0: Demo app When the experiments yielded promising results, they would immediately deploy the models to internal clients. This is the phase where they would expose the MVP with automation and structured engineering code put on top of the experiments they run. They integrate with neptune.ai

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The MLOps Blog

JUNE 27, 2023

” – James Tu, Research Scientist at Waabi Play with this project live For more: Dive into documentation Get in touch if you’d like to go through a custom demo with your team Comet ML Comet ML is a cloud-based experiment tracking and optimization platform.

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Viso.ai

FEBRUARY 27, 2024

Since its inception in 2015, the YOLO (You Only Look Once) object-detection algorithm has been closely followed by tech enthusiasts, data scientists, ML engineers, and more, gaining a massive following due to its open-source nature and community contributions.

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The MLOps Blog

JULY 4, 2024

Further, talking to data scientists and ML engineers, I noticed quite a bit of confusion around RAG systems and terminology. This is what you see in most PoCs or demos for LLM systems: a simple Langchain notebook where everything just works. I often have to explain the ideas and concepts around RAG to business stakeholders.

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LLM Large Language Models Machine Learning Explainability 64

Viso.ai

JANUARY 30, 2024

It enables enterprises to create and implement computer vision solutions , featuring built-in ML tools for data collection, annotation, and model training. Learn more about Viso Suite and book a demo. This is a bigger deal with raw or unstructured data that engineers and developers might be using to feed the machine learning program.

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The MLOps Blog

JANUARY 24, 2024

It offers a single place to track, compare, store, and collaborate on experiments so that Data Scientists can develop production-ready models faster and ML Engineers can access model artifacts instantly in order to deploy them to production.

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Metadata Python Data Scientist ML 59

Viso.ai

MARCH 29, 2024

MLflow is an open-source platform designed to manage the entire machine learning lifecycle, making it easier for ML Engineers, Data Scientists, Software Developers, and everyone involved in the process. Machine learning operations (MLOps) are a set of practices that automate and simplify machine learning (ML) workflows and deployments.

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Machine Learning ML Automation Data Scientist 52

Viso.ai

FEBRUARY 11, 2024

Viso Suite utilizes all popular object detection models available, including Detectron2, to get started, book a demo. With Viso Suite, enterprises can get started using computer vision to solve business challenges without any code. Viso Suite : the only end-to-end computer vision platform Detectron2: What’s Inside?

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The MLOps Blog

OCTOBER 20, 2023

And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. Nevertheless, many data scientists will agree that they can be really valuable – if used well. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis.

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The MLOps Blog

JANUARY 30, 2025

See in app Full screen preview Check the documentation Play with an interactive example project Get in touch to go through a custom demo with our engineering team Cyclical cosine schedule Returning to a high learning rate after decaying to a minimum is not a new idea in machine learning.

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The MLOps Blog

MAY 10, 2023

It’s a great option for data scientists and ML engineers that need to manage their trained models, because it gives them collaboration features, user-friendly interface, and model versioning capabilities. In this example, I’ll use the Neptune. You can set up a free account here or learn more about the tool here.

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The MLOps Blog

OCTOBER 3, 2023

I see so many of these job seekers, especially on the MLOps side or the ML engineer side. Thus, each team that was involved in MLOps or the ML platform initiatives had what we called “embedded MLOps engineers. They were kind of close to an ML engineering role, but not really. It’s two things.

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ML Data Scientist Machine Learning Data Science 52

The MLOps Blog

MAY 9, 2023

One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times. Kale v0.7.0.

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AWS Machine Learning Blog

SEPTEMBER 26, 2024

Amazon SageMaker Studio provides a single web-based visual interface where different personas like data scientists, machine learning (ML) engineers, and developers can build, train, debug, deploy, and monitor their ML models. ML engineers require access to intermediate model artifacts stored in Amazon S3 from past training jobs.

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AWS Machine Learning Blog

APRIL 19, 2024

Solution overview For this demo, we use the SageMaker controller to deploy a copy of the Dolly v2 7B model and a copy of the FLAN-T5 XXL model from the Hugging Face Model Hub on a SageMaker real-time endpoint using the new inference capabilities. About the Authors Rajesh Ramchander is a Principal ML Engineer in Professional Services at AWS.

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The MLOps Blog

MARCH 21, 2023

As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale. In this comprehensive guide, we’ll explore everything you need to know about machine learning platforms, including: Components that make up an ML platform.

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Mlearning.ai

MAY 3, 2023

We create a demo APP illustrating the same. Snippet for creating the Multipage Web APP (Image by Author) Getting Started For using the APP, refer the instructions provided here —  [link] APP DEMO For running the APP run the command “ python app.py ” from within the cloned repository. The code below illustrates the same.

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Large Language Models Python Auto-complete Natural Language Processing 52

The MLOps Blog

DECEMBER 29, 2022

Does it mean that the production code has to be rewritten by, for example, ML engineers manually to be optimized for GPU with each update? I recommend a hybrid approach, so maybe if you’re, again, I’m speaking to seed-stage series A companies like early-stage products, but look at you’re doing a demo application.

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Viso.ai

DECEMBER 21, 2023

Each of these individuals serves as an inspiration for aspiring AI and ML engineers breaking into the field. If you are already deploying computer vision projects or looking to get ahead, request a demo for your company! Our no-code, end-to-end technology was recently featured on TechCrunch.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

With the unification of SageMaker Model Cards and SageMaker Model Registry, architects, data scientists, ML engineers, or platform engineers (depending on the organization’s hierarchy) can now seamlessly register ML model versions early in the development lifecycle, including essential business details and technical metadata.

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