AI News

JULY 28, 2023

AI and machine learning are reshaping the job landscape, with higher incentives being offered to attract and retain expertise amid talent shortages. According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years.

ML 192

ML ML Engineer Natural Language Processing Big Data 192

Flipboard

MAY 31, 2023

Learn how to easily build any AI model and customize your own LLM in just a few lines of code with a declarative approach to machine learning.

ML Engineer 91

ML Engineer ML Machine Learning LLM 91

AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

Machine Learning 104

Machine Learning ML Engineer DevOps ML 104

ODSC - Open Data Science

SEPTEMBER 21, 2023

The majority of us who work in machine learning, analytics, and related disciplines do so for organizations with a variety of different structures and motives. The following is an extract from Andrew McMahon’s book , Machine Learning Engineering with Python, Second Edition.

Machine Learning 98

Machine Learning ML Engineer ML Data Science 98

AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

ML 106

ML Generative AI AI AI 106

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.

Machine Learning 112

Machine Learning DevOps Data Quality Data Scientist 112

Marktechpost

JANUARY 31, 2024

Data scientists and ML engineers often need help to build full-stack applications. Still, they may need more skills or time to learn new languages or frameworks to create user-friendly web applications. It is a Python-based framework for data scientists and machine learning engineers.

Data Scientist 133

Data Scientist Machine Learning Python ML Engineer 133

Pickl AI

APRIL 19, 2023

Machine Learning is the part of Artificial Intelligence and computer science that emphasizes on the use of data and algorithms, imitating the way humans learn and improving accuracy. Machine Learning is becoming increasingly popular and crucial in today’s market for effective productivity and decision-making processes.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

Marktechpost

JANUARY 10, 2024

Automated Machine Learning (AutoML) has been introduced to address the pressing need for proactive and continual learning in content moderation defenses on the LinkedIn platform. It is a framework for automating the entire machine-learning process, specifically focusing on content moderation classifiers.

Machine Learning 89

Machine Learning Continuous Learning Automation ML Engineer 89

ODSC - Open Data Science

FEBRUARY 9, 2023

That responsibility usually falls in the hands of a role called Machine Learning (ML) Engineer. Having empathy for your ML Engineering colleagues means helping them meet operational constraints. To continue with this analogy, you might think of the ML Engineer as the data scientist’s “editor.”

Data Scientist 105

Data Scientist Machine Learning ML Engineer ML 105

Marktechpost

AUGUST 8, 2023

In the ever-evolving landscape of machine learning, feature management has emerged as a key pain point for ML Engineers at Airbnb. Chronon empowers ML practitioners to define features and centralize data computation for model training and production inference, guaranteeing accuracy and consistency throughout the process.

Machine Learning 98

Machine Learning ML Engineer Data Ingestion ML 98

Marktechpost

JULY 19, 2023

In the actual world, machine learning (ML) systems can embed issues like societal prejudices and safety worries. Stakeholders such as ML engineers, designers, and domain experts must work together to identify a model’s expected and potential faults. Thus it should scale well to great deployed scenarios.

Machine Learning 52

Machine Learning ML Python Metadata 52

Pickl AI

APRIL 5, 2023

Machine Learning is one of the transforming technologies that has had a ripple effect across the industry domain. ML forms the underlying platform for several new developments. Hence, it has also triggered the demand for ML experts. Acquiring Machine Learning skills can have catalytic impact on your professional growth.

Machine Learning 52

Machine Learning ML Engineer ML Data Scientist 52

AI News

MARCH 8, 2024

Hugging Face , the startup behind the popular open source machine learning codebase and ChatGPT rival Hugging Chat, is venturing into new territory with the launch of an open robotics project. Until now, Hugging Face has primarily focused on software offerings like its machine learning codebase and open-source chatbot.

Robotics 230

Robotics Big Data Deep Learning ML Engineer 230

Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

Machine Learning 94

Machine Learning BERT Deep Learning ML Engineer 94

ODSC - Open Data Science

FEBRUARY 22, 2024

Today we are excited to bring you just a few of the machine learning sessions you’ll be able to participate in if you attend. In this session, you’ll take a deep dive into the three distinct types of Feature Stores and their uses in the machine learning ecosystem. Check them out below. Who Wants to Live Forever?

Machine Learning 52

Machine Learning Data Science Python ML 52

Snorkel AI

APRIL 27, 2023

Here at Snorkel AI, we devote our time to building and maintaining our machine-learning development platform, Snorkel Flow. Snorkel Flow handles intense machine learning workloads, and we’ve built our infrastructure on a foundation of Kubernetes—which was not designed with machine learning in mind.

Machine Learning 97

Machine Learning ML AI AI 97

Snorkel AI

APRIL 27, 2023

Here at Snorkel AI, we devote our time to building and maintaining our machine-learning development platform, Snorkel Flow. Snorkel Flow handles intense machine learning workloads, and we’ve built our infrastructure on a foundation of Kubernetes—which was not designed with machine learning in mind.

Machine Learning 96

Machine Learning ML AI AI 96

Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Data Science enhances ML accuracy through preprocessing and feature engineering expertise.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Analytics Vidhya

OCTOBER 6, 2023

Ray streamlines complex tasks for ML engineers, data scientists, and developers. Its versatility spans data processing, model training, hyperparameter tuning, deployment, and reinforcement learning. Python Ray is a dynamic framework revolutionizing distributed computing.

Python 287

Python ML Engineer Data Scientist ML 287

TheSequence

JANUARY 26, 2024

Want to know how FanDuel engineered and built a powerful ML platform to handle hundreds of millions of data rows and evaluate millions of results—all to deliver personalized experiences to their users?

Machine Learning 52

Machine Learning ML Engineer ML 52

Heartbeat

SEPTEMBER 6, 2023

Experimenting with Comet, a machine learning platform Photo by Donny Jiang on Unsplash Creating a machine learning model is easy, but that’s not what machine learning is all about. There are machine learning platforms that can perform all these tasks, and Comet is one such platform.

Machine Learning 52

Machine Learning Deep Learning Auto-complete Data Scientist 52

Marktechpost

OCTOBER 11, 2023

The team started with a collection of 15 ML engineering projects spanning various fields, with experiments that are quick and cheap to run. Also, don’t forget to join our 31k+ ML SubReddit , 40k+ Facebook Community, Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.

Machine Learning 104

Machine Learning AI Researcher AI Research Convolutional Neural Networks 104

Heartbeat

OCTOBER 30, 2023

Ensuring Long-Term Performance and Adaptability of Deployed Models Source: [link] Introduction When working on any machine learning problem, data scientists and machine learning engineers usually spend a lot of time on data gathering , efficient data preprocessing , and modeling to build the best model for the use case.

Machine Learning 52

Machine Learning Data Drift ML Data Scientist 52

Mlearning.ai

JULY 29, 2023

Schedule Batch Inference of Machine Learning Model on Azure Cloud with Container Services and Logic App Photo by Victoire Joncheray on Unsplash I. This approach is heavily inspired by the book Designing Machine Learning Systems by Chip Huyen , a go-to resource for any ML Engineer.

Machine Learning 52

Machine Learning DevOps ML ML Engineer 52

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?

ML 52

ML ML Engineer Software Engineer Data Scientist 52

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 144

Data Science DevOps Machine Learning Data Scientist 144

AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

ML 99

ML Python Deep Learning Machine Learning 99

TheSequence

JULY 7, 2023

Discover FanDuel's journey in building a powerful ML platform for personalized experiences. PT to learn how they scaled their platform and lessons learned. Join the webinar on July 11 at 9 a.m. Can’t make the live webinar? Register anyway to access the on-demand video later.

Machine Learning 52

Machine Learning ML Engineer ML 52

deepsense.ai

APRIL 18, 2023

As it does every year, the event is focused on the exchange of experiences between machine learning practitioners and, most importantly, an effective update of knowledge in the rapidly changing discipline of data analysis. Once again, deepsense.ai has become GHOST Day: AMLC conference platinum partner. The post deepsense.ai

Machine Learning 52

Machine Learning Data Scientist Large Language Models ML Engineer 52

Towards AI

JULY 19, 2023

How to Maximize ML Project Success with Efficient Scoping? | Lifecycle of a Machine Learning Project. This shows that scoping the projects is one of the most important steps before starting a machine learning project. What can you recommend to him as an ML Engineer? Let’s speak examples.

ML 80

ML Machine Learning ML Engineer Explainability 80

Unite.AI

JUNE 29, 2023

Business leaders in today's tech and startup scene know the importance of mastering AI and machine learning. By tapping into AI and machine learning services offered by cloud providers, businesses can unlock fresh growth opportunities, automate their processes, and steer their cost-cutting initiatives.

ML 262

ML AI AI Machine Learning 262

AWS Machine Learning Blog

NOVEMBER 21, 2023

By taking care of the undifferentiated heavy lifting, SageMaker allows you to focus on working on your machine learning (ML) models, and not worry about things such as infrastructure. Prior to working at Amazon Music, Siddharth was working at companies like Meta, Walmart Labs, Rakuten on E-Commerce centric ML Problems.

ML 82

ML Deep Learning Machine Learning DevOps 82

Snorkel AI

JUNE 30, 2023

Jack Zhou, product manager at Arize , gave a lightning talk presentation entitled “How to Apply Machine Learning Observability to Your ML System” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. So ML ends up being a huge part of many large companies’ core functions. Our agenda.

Machine Learning 52

Machine Learning ML Data Quality Data Drift 52

Snorkel AI

JUNE 30, 2023

Jack Zhou, product manager at Arize , gave a lightning talk presentation entitled “How to Apply Machine Learning Observability to Your ML System” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. So ML ends up being a huge part of many large companies’ core functions. Our agenda.

Machine Learning 52

Machine Learning ML Data Quality Data Drift 52

Analytics Vidhya

FEBRUARY 21, 2022

Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s). Make it simple, for every […].

ML Engineer 311

ML Engineer Data Scientist Deep Learning Data Science 311

Heartbeat

SEPTEMBER 18, 2023

Unleashing Innovation and Success: Comet — The Trusted ML Platform for Enterprise Environments Machine learning (ML) is a rapidly developing field, and businesses are increasingly depending on ML platforms to fuel innovation, improve efficiency, and mine data for insights.

ML 52

ML Data Scientist ML Engineer Machine Learning 52