ODSC - Open Data Science

OCTOBER 7, 2024

So let’s explore how MLOps for software engineers addresses these hurdles, enabling scalable, efficient AI development pipelines. One of the key benefits of MLOps for software engineers is its focus on version control and reproducibility. But first, let’s get a quick overview of the MLOps lifecycle.

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Software Engineer Data Ingestion Machine Learning Data Scientist 52

Flipboard

SEPTEMBER 12, 2023

AI applications are booming. But to keep them from breaking, the data flowing into those apps needs to be high-quality — that is, reliable, complete and accurate. That’s the problem Gable.ai is poised to solve as the Seattle-based startup launches out of stealth today with $7 million in seed …

Software Engineer 165

Software Engineer ML AI AI 165

Marktechpost

SEPTEMBER 11, 2024

Large Language Models (LLMs) have revolutionized software engineering, demonstrating remarkable capabilities in various coding tasks. While recent efforts have produced autonomous software agents based on LLMs for end-to-end development tasks, these systems are typically designed for specific Software Engineering (SE) tasks.

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Software Engineer Software Development Large Language Models LLM 116

Mlearning.ai

MAY 27, 2023

Why data scientists and analysts ought to have a working knowledge of software engineering in Python? There are several good reasons why data scientists and analysts, particularly Python, need a solid grounding in software engineering ideas and techniques. To start this post, I want to start with the following question.

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Software Engineer Data Scientist Software Development Machine Learning 52

ODSC - Open Data Science

OCTOBER 9, 2024

The rapid evolution of AI is transforming nearly every industry/domain, and software engineering is no exception. But how so with software engineering you may ask? These technologies are helping engineers accelerate development, improve software quality, and streamline processes, just to name a few.

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Software Engineer Software Development DevOps ETL 40

Heartbeat

FEBRUARY 29, 2024

After closely observing the software engineering landscape for 23 years and engaging in recent conversations with colleagues, I can’t help but feel that a specialized Large Language Model (LLM) is poised to power the following programming language revolution.

Software Engineer 52

Software Engineer Software Development LLM Large Language Models 52

Marktechpost

MARCH 2, 2024

These platforms assess the functional correctness of code generated by LLMs and emphasize the importance of aligning LLMs with the specific needs of software engineering tasks. Join our 38k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Software Engineer 105

Software Engineer Large Language Models Software Development LLM 105

Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

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Data Science ML ML Engineer Data Scientist 108

Analytics Vidhya

JUNE 7, 2023

Google AI has made a groundbreaking discovery in the realm of software engineering. In a new research project, they introduce DIDACT, a revolutionary technique that utilizes large machine learning (ML) models to enhance software development activities.

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Software Development Software Engineer Machine Learning ML 299

ODSC - Open Data Science

SEPTEMBER 12, 2024

Must-Use Data Visualization Datasets, AI Frameworks for Software Engineering, DynGAN, and 50% Off ODSC West 12 Must-Use Datasets for Data Visualization in 2024 Need to practice making sense of your data? These open-source datasets for data visualization will help you visualize your data and make attractive, informative images.

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Software Engineer Data Science Machine Learning AI 40

AWS Machine Learning Blog

NOVEMBER 7, 2024

Operating such large-scale forecasting requires resilient, reusable, reproducible, and automated machine learning (ML) workflows with fast experimentation and continuous improvements. To improve forecasting accuracy, all involved ML models need to be retrained, and predictions need to be produced weekly, and in some cases daily.

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ML Machine Learning Automation Data Scientist 111

Marktechpost

SEPTEMBER 25, 2024

With the rapid advancement of technology, surpassing human abilities in tasks like image classification and language processing, evaluating the energy impact of ML is essential. Historically, ML projects prioritized accuracy over energy efficiency, contributing to increased energy consumption.

Machine Learning 105

Machine Learning ML Software Engineer ML Engineer 105

Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. Meet the MLOps Engineer: the orchestrating the seamless integration of ML models into production environments, ensuring scalability, reliability, and efficiency.

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Software Engineer DevOps Machine Learning ML 182

Google Research AI blog

MAY 23, 2023

Posted by Alexander Frömmgen, Staff Software Engineer, and Lera Kharatyan, Senior Software Engineer, Core Systems & Experiences Code-change reviews are a critical part of the software development process at scale, taking a significant amount of the code authors’ and the code reviewers’ time.

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ML Software Engineer Automation Software Development 140

Towards AI

JULY 2, 2024

What are the most important skills for an ML Engineer? Well, I asked ML engineers at all these companies to share what they consider the top skills… And I’m telling you, there were a lot of answers I received and I bet you didn’t even think of many of them!

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ML Engineer ML Software Engineer Python 77

Mlearning.ai

DECEMBER 21, 2023

Design patterns in software engineering are typical solutions to common problems in software design. They represent best practices, evolved over time, and are a toolkit for software developers to solve common problems efficiently. Source: Image by the Author What are Design Patterns? How to Get Started?

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Software Engineer Software Development DevOps Algorithm 52

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. Holistic design for ML systems To mitigate potential issues during production deployment, a holistic approach to machine learning system design is recommended. Aside neptune.ai

Software Engineer 52

Software Engineer Machine Learning ETL Data Scientist 52

TheSequence

FEBRUARY 5, 2024

Want to know how Plaid, a leading fintech company, built the ML infrastructure that powers Signal, its payment fraud detection and prevention application? Then watch this virtual fireside chat on demand!

ML 52

ML Software Engineer 52

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. I started as a full-stack developer but have gradually moved toward data and ML engineering.

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ML Data Scientist Automation Software Development 59

Unite.AI

NOVEMBER 14, 2023

Similar to how early computer scientists transitioned from a focus on electrical engineering to more abstract concepts, future programmers may view detailed coding as obsolete. In areas like image generation diffusion model like Runway ML , DALL-E 3 , shows massive improvements. Introducing, Motion Brush. using GPT-3.

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Large Language Models Software Engineer Computer Scientist ChatGPT 331

AWS Machine Learning Blog

APRIL 26, 2023

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Challenges Customers may face several challenges when implementing machine learning (ML) solutions.

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ML Machine Learning Data Science Data Drift 116

Flipboard

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. Deploy traditional models to SageMaker endpoints In the following examples, we showcase how to use ModelBuilder to deploy traditional ML models.

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ML Python Machine Learning Algorithm 167

TheSequence

SEPTEMBER 8, 2023

Want to know how Plaid, a leading fintech company, built the ML infrastructure that powers Signal, its payment fraud detection and prevention application? Technical solutions they adopted, including a new ML platform that allows for generating training datasets and designed for feature freshness and seamless large-scale production.

ML 52

ML Software Engineer 52

AWS Machine Learning Blog

APRIL 20, 2023

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. Based on Inference Recommender’s instance type recommendations, we can find the right real-time serving ML instances that yield the right price-performance for this use case.

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ML Auto-classification Python Auto-complete 95

Marktechpost

JULY 11, 2024

Software engineering is a dynamic field focused on the systematic design, development, testing, and maintenance of software systems. Recently, advancements in large language models (LLMs) have revolutionized these processes, enabling more sophisticated automation of software development tasks. Check out the Paper.

Software Development 105

Software Development Software Engineer Large Language Models LLM 105

Google Research AI blog

APRIL 27, 2023

Posted by Babak Behsaz, Software Engineer, and Andrew Carroll, Product Lead, Genomics The combination of the environment an individual experiences and their genetic predispositions determines the majority of their risk for various diseases. Much of the rich data from these spirograms is discarded in this analysis of lung function.

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ML Deep Learning Software Engineer 99

Marktechpost

MARCH 19, 2024

The software development sector stands at the dawn of a transformation powered by artificial intelligence (AI), where AI agents perform development tasks. This transformation is not just about incremental enhancements but a radical reimagining of how software engineering tasks are approached, executed, and delivered.

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Software Development Artificial Intelligence Artificial Intelligence Automation 145

Google Research AI blog

MAY 19, 2023

Posted by Natalia Ponomareva and Alex Kurakin, Staff Software Engineers, Google Research Large machine learning (ML) models are ubiquitous in modern applications: from spam filters to recommender systems and virtual assistants. Therefore, protecting the privacy of the training data is critical to practical, applied ML.

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ML Neural Network Algorithm Machine Learning 102

TheSequence

NOVEMBER 3, 2023

Join the global ML community at this virtual event—speakers from companies like HelloFresh, Lidl Digital, Meta, PepsiCo, Riot Games, and more will share best practices around building platforms and architectures for production ML. apply(ops) is just around the corner!

ML Engineer 52

ML Engineer ML Software Engineer Software Development 52

Marktechpost

OCTOBER 16, 2023

Evaluating the proficiency of language models in addressing real-world software engineering challenges is essential for their progress. This highlights the pressing need for further advancements in language models to enable practical and intelligent software engineering solutions.

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Machine Learning Software Engineer Python AI Research 143

Marktechpost

AUGUST 11, 2024

Successfully addressing this challenge is essential for advancing automated software engineering, particularly in enabling LLMs to handle real-world software development tasks that require a deep understanding of large-scale repositories. Check out the Paper and GitHub. If you like our work, you will love our newsletter.

Artificial Intelligence 124

Artificial Intelligence Artificial Intelligence LLM Software Engineer 124

Unite.AI

APRIL 22, 2024

This framework combines artificial intelligence (AI), machine learning (ML), and decision management (DM) – all strategies that enable software businesses to deliver high-quality products to market faster. The fact that this approach to application development is augmenting the adoption of AI/ML systems is further proof-of-concept.

Software Engineer 246

Software Engineer ML Algorithm Artificial Intelligence 246

Marktechpost

MAY 10, 2024

Language models (LMs) have gained traction as aids in software engineering, where users act as intermediaries between LMs and computers, refining LM-generated code based on computer feedback. Recent advancements depict LMs functioning autonomously in computer environments, potentially expediting software development.

Software Development 126

Software Development Software Engineer ML Large Language Models 126

Google Research AI blog

MAY 15, 2023

Posted by Candice Schumann, Software Engineer, and Gbolahan O. How do we effectively annotate skin tone for use in inclusive machine learning (ML)? The images are not to be used to train ML models. depending on their location or culture) and thus is complicated to annotate.

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ML Computer Vision Software Engineer Machine Learning 109

Mlearning.ai

FEBRUARY 23, 2023

Optimizing My Workflow with Essential Tools and Configurations Continue reading on MLearning.ai »

Software Engineer 52

Software Engineer Software Development ML 52

IBM Journey to AI blog

AUGUST 12, 2024

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). ML technologies help computers achieve artificial intelligence. However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

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Big Data DevOps Automation Machine Learning 278

TheSequence

MAY 26, 2023

Want to connect with the ML engineering community and learn best practices from ML practitioners on how to build risk and fraud detection systems? Francisco Arceo, Engineering Manager at Affirm , will discuss the common pitfalls and share simple approaches to avoiding them. Need more reasons to sign up? REGISTER NOW

ML 52

ML ML Engineer Software Engineer Data Scientist 52