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. What is MLOps?

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Data Science DevOps Machine Learning Data Scientist 148

AI News

MARCH 8, 2024

A job listing for an “Embodied Robotics Engineer” sheds light on the project’s goals, which include “designing, building, and maintaining open-source and low cost robotic systems that integrate AI technologies, specifically in deep learning and embodied AI.”

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Robotics Big Data Deep Learning ML Engineer 227

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.

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ML Data Scientist ML Engineer Machine Learning 52

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.

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Machine Learning ML Engineer DevOps ML 107

Flipboard

NOVEMBER 28, 2023

Artificial intelligence (AI) is a rapidly evolving field with the potential to improve and transform many aspects of society. In fact, a typical AI system is likely to be based on multiple different ML models working together, and an organization might be looking to build multiple different AI systems. About the Authors Mia C.

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Responsible AI Artificial Intelligence Artificial Intelligence AI 144

Towards AI

AUGUST 25, 2023

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In a nutshell, AI Engineering is the application of software engineering best practices to the field of AI.

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Software Engineer Machine Learning Neural Network Artificial Intelligence 97

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. Zeno works together with other systems and combines the methods of others.

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Machine Learning ML Python Metadata 52

AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts.

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ML ML Engineer Machine Learning Data Scientist 108

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.”

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Data Scientist Machine Learning ML Engineer ML 105

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. Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Consequently.

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Machine Learning ML Engineer Data Scientist ML 52

Towards AI

AUGUST 24, 2023

Common mistakes and misconceptions about learning AI/ML Markus Spiske on Unsplash A common misconception of beginners is that they can learn AI/ML from a few tutorials that implement the latest algorithms, so I thought I would share some notes and advice on learning AI. Trying to code ML algorithms from scratch.

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Software Engineer Neural Network Algorithm AI Engineer 95

ODSC - Open Data Science

SEPTEMBER 21, 2023

Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. Some typical examples are given in the following table, along with some discussion as to whether or not ML would be an appropriate tool for solving the problem: Figure 1.1:

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Machine Learning ML Engineer ML Data Science 98

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.

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Machine Learning ML Engineer Data Ingestion ML 94

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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Marktechpost

JANUARY 31, 2024

Data scientists and ML engineers often need help to build full-stack applications. These professionals typically have a firm grasp of data and AI algorithms. Still, they may need more skills or time to learn new languages or frameworks to create user-friendly web applications.

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Data Scientist Machine Learning Python ML Engineer 126

Unite.AI

NOVEMBER 10, 2023

Artificial intelligence keeps booming, and if it continues permeating into every industry, it will completely transform the way we live. The basic idea is that these tools can be integrated by business developers (not ML specialists), which will allow us to quickly test the hypothesis of whether AI brings the expected effect or not.

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AWS Machine Learning Blog

MARCH 22, 2024

The AI Content Generator powered by Amazon Bedrock is an app available on the Contentful Marketplace that allows users to create, rewrite, summarize, and translate content using cutting-edge generative artificial intelligence (AI) models available and accessible through Amazon Bedrock in a simple and secure manner.

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Large Language Models Natural Language Processing Software Engineer NLP 91

Unite.AI

FEBRUARY 28, 2024

LLMs are a class of artificial intelligence systems that have been trained on massive text corpora, allowing them to generate remarkably human-like text and engage in natural conversations. Foster closer collaboration between security teams and ML engineers to instill security best practices.

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AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. These five risks are insecure output handling, supply chain vulnerabilities, sensitive information disclosure, excessive agency, and overreliance.

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Pickl AI

JANUARY 30, 2023

It’s a universal programming language that finds application in different technologies like AI, ML, Big Data and others. Versatile programming language- You can use Python for web development, Data Science, Machine Learning, Artificial Intelligence, finance and in many other domains. In fact, Python finds multiple applications.

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Python DevOps Machine Learning Automation 97

AWS Machine Learning Blog

NOVEMBER 16, 2023

One of the key drivers of Philips’ innovation strategy is artificial intelligence (AI), which enables the creation of smart and personalized products and services that can improve health outcomes, enhance customer experience, and optimize operational efficiency.

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Data Scientist ML Data Science Automation 92

Pickl AI

JULY 14, 2023

Artificial Intelligence has been able to gain immense momentum today and is transforming every industry in the world. Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

AWS Machine Learning Blog

APRIL 11, 2023

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science.

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ML Engineer ML Data Scientist Machine Learning 73

ODSC - Open Data Science

JANUARY 10, 2024

Takeaways include: The dangers of using post-hoc explainability methods as tools for decision-making, and where traditional ML falls short. Participants will walk away with a solid grasp of feature stores, equipped with the knowledge to drive meaningful insights and enhancements in their real-world ML platforms and projects.

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AWS Machine Learning Blog

AUGUST 4, 2023

SageMaker integration SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. Rachna Chadha is a Principal Solutions Architect AI/ML in Strategic Accounts at AWS.

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Data Scientist ML ETL AI 73

TheSequence

NOVEMBER 5, 2023

AlphaFold stands as a prime example of innovation at the intersection of the two hottest trends in the current market: artificial intelligence and digital biology. 🛠 Real World ML LLM Architectures at GitHub GitHub ML engineers discuss the architecture of LLMs apps —> Read more.

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ML ML Engineer Chatbots Big Data 52

Towards AI

APRIL 27, 2023

Nothing in the world motivates a team of ML engineers and scientists to spend the required amount of time in data annotation and labeling. There are a lot more complexities at this stage. You can read a very famous publication by the Google research team titled “Everyone wants to do the model work, not the data work”.

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Automation Auto-complete Computer Vision ML Engineer 91

AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. GitHub serves as a centralized location to store, version, and manage your ML code base.

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ML Automation Metadata Software Development 103

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.

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Machine Learning AI Researcher AI Research Convolutional Neural Networks 104

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms. We pay our contributors, and we don't sell ads.

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Data Scientist Machine Learning Big Data Algorithm 52

Chatbots Life

MAY 16, 2023

10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland. Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision. Services : Conversational AI, Chatbots, Voice Assistants, Digital Humans.

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Generative AI Chatbots Conversational AI Software Development 98

Unite.AI

FEBRUARY 15, 2024

The people aspect underlines the need for skilled AI/ML engineers, data scientists, and software developers. Data readiness emphasizes the importance of high-quality training data, while concerns about data privacy and security are also raised.

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Generative AI ML Engineer AI AI 100

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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ODSC - Open Data Science

MARCH 27, 2023

Learn about the flow, difficulties, and tools for performing ML clustering at scale Ori Nakar | Principal Engineer, Threat Research | Imperva Given that there are billions of daily botnet attacks from millions of different IPs, the most difficult challenge of botnet detection is choosing the most relevant data.

Machine Learning 98

Machine Learning Data Ingestion Explainability ML 98

Towards AI

JANUARY 27, 2024

By configuring hyperparameters as per specific requirements and leveraging the library’s customizable search space, AutoKeras proves to be a valuable tool for data scientists and ML engineers. References [link] [link] U+2709️mkk.rakesh@gmail.com Join thousands of data leaders on the AI newsletter.

Deep Learning 100

Deep Learning Explainability ML Engineer Data Scientist 100

ODSC - Open Data Science

FEBRUARY 22, 2024

Key points of this talk are: In this talk, we will focus on: The dangers of using post-hoc explainability methods as tools for decision making, and how traditional ML isn’t suited in situations where want to perform interventions on the system. technical architecture that simplifies the process of managing real-time ML models and features.

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Machine Learning Data Science Python ML 52

ODSC - Open Data Science

FEBRUARY 2, 2023

Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on. They’re looking for people who know all related skills, and have studied computer science and software engineering.

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