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 135

Towards AI

MARCH 14, 2024

I mean, ML engineers often spend most of their time handling and understanding data. So, how is a data scientist different from an ML engineer? Well, there are three main reasons for this confusing overlap between the role of a data scientist and the role of an ML engineer.

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Data Science ML Engineer Data Scientist ML 105

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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IBM Journey to AI blog

AUGUST 12, 2024

Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data. The process includes activities such as anomaly detection, event correlation, predictive analytics, automated root cause analysis and natural language processing (NLP).

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Big Data DevOps Automation Machine Learning 266

Towards AI

NOVEMBER 8, 2024

Data preparation isn’t just a part of the ML engineering process — it’s the heart of it. Data is a key differentiator in ML projects (more on this in my blog post below). We don’t have better algorithms; we just have more data. This post dives into key steps for preparing data to build real-world ML systems.

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Data Ingestion Metadata ML Engineer ML 111

Towards AI

FEBRUARY 18, 2025

In this post, I want to shift the conversation to how Deepseek is redefining the future of machine learning engineering. It has already inspired me to set new goals for 2025, and I hope it can do the same for other ML engineers. It is fascinating what Deepseek has achieved with their top noche engineering skill.

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Towards AI

JANUARY 30, 2024

ML Engineers(LLM), Tech Enthusiasts, VCs, etc. Anybody previously acquainted with ML terms should be able to follow along. The algorithm works by optimizing the reward policy and then fine-tuning the unsupervised LLM according to reward maximization of such human-reinforced preference feedback. How advanced is this post?

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Explainability ML Engineer LLM ML 111

Towards AI

FEBRUARY 15, 2024

AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job. Skills Needed as an AI Engineer As an AI engineer, you require a blend of soft and hard skills.

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AI Engineer Software Engineer Artificial Intelligence Artificial Intelligence 111

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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Marktechpost

JANUARY 10, 2024

Rather than relying on groundbreaking algorithmic changes, the emphasis is on continual learning and iterative improvements. It also automates feature engineering, a task traditionally handled solely by ML engineers, saving time and reducing the risk of errors.

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Machine Learning Continuous Learning ML Engineer Automation 102

O'Reilly Media

JANUARY 17, 2023

Given that, what would you say is the job of a data scientist (or ML engineer, or any other such title)? But first, let’s talk about the typical ML workflow. You know the drill: pull some data, carve it up into features, feed it into one of scikit-learn’s various algorithms. Building Models.

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Automation Robotics Data Scientist ML 145

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. After all, this is what machine learning really is; a series of algorithms rooted in mathematics that can iterate some internal parameters based on data.

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Machine Learning ML Engineer ML Data Science 98

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.

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Machine Learning BERT Deep Learning ML Engineer 123

ODSC - Open Data Science

FEBRUARY 24, 2023

Apache Superset GitHub | Website Apache Superset is a must-try project for any ML engineer, data scientist, or data analyst. Algorithm-visualizer GitHub | Website Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. The no-code visualization builds are a handy feature.

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Data Analysis Data Science Business Intelligence Python 126

ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. This will lead to algorithm development for any machine or deep learning processes.

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Data Science Data Scientist Big Data Machine Learning 98

Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. In ML, there are a variety of algorithms that can help solve problems. Any competent software engineer can implement any algorithm. 12, 2014. [3]

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Machine Learning Software Engineer Neural Network Data Science 98

AWS Machine Learning Blog

MARCH 9, 2023

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. This has led to the emergence of a data-centric approach to ML and various techniques to improve model performance by focusing on data requirements.

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ML Engineer Data Scientist Convolutional Neural Networks ML 92

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. As businesses across industries increasingly embrace AI and ML to gain a competitive edge, the demand for MLOps Engineers has skyrocketed.

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Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

DECEMBER 10, 2024

You can try this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can be deployed with one click for running inference. In this post, we walk through how to discover, deploy, and use the Pixtral 12B model for a variety of real-world vision use cases.

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ML Generative AI Computer Vision ML Engineer 99

AWS Machine Learning Blog

DECEMBER 9, 2024

MLflow , a popular open-source tool, helps data scientists organize, track, and analyze ML and generative AI experiments, making it easier to reproduce and compare results. SageMaker is a comprehensive, fully managed ML service designed to provide data scientists and ML engineers with the tools they need to handle the entire ML workflow.

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ML Data Scientist Machine Learning Software Engineer 90

Unite.AI

NOVEMBER 10, 2023

It is key to remember that AI is an algorithm, which analyzes and adjusts to the data we provide. Leverage the solutions that already exist Many companies aim to, right away, design their own machine learning algorithms. The basic scenario for data collection is as follows: Understand what data we might need to implement AI.

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AI AI ML Chatbots 182

Towards AI

JANUARY 6, 2025

AI engineering professional certificate by IBM AI engineering professional certificate from IBM targets fundamentals of machine learning, deep learning, programming, computer vision, NLP, etc. However, you are expected to possess intermediate coding experience and a background as an AI ML engineer; to begin with the course.

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Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

AWS Machine Learning Blog

FEBRUARY 21, 2025

There are various techniques of preference alignment, including proximal policy optimization (PPO), direct preference optimization (DPO), odds ratio policy optimization (ORPO), group relative policy optimization (GRPO), and other algorithms, that can be used in this process. The following diagram compares predictive AI to generative AI.

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LLM AI AI Data Scientist 81

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.

Machine Learning 52

Machine Learning ML Engineer Data Scientist ML 52

ODSC - Open Data Science

APRIL 1, 2025

Adaptive RAG Systems with Knowledge Graphs: Building Smarter LLM Pipelines David vonThenen, Senior AI/ML Engineer at DigitalOcean Unlock the full potential of Retrieval-Augmented Generation by embedding adaptive reasoning with knowledge graphs. Youll explore the latest algorithms, training setups, and real-world applications.

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Neural Network LLM Software Engineer AI 52

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field. million by 2030, with a remarkable CAGR of 44.8%

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Machine Learning Neural Network ML Engineer Algorithm 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

Verifiable evaluation scores are provided across text generation, summarization, classification and question answering tasks, including customer-defined prompt scenarios and algorithms. It also integrates with Machine Learning and Operation (MLOps) workflows in Amazon SageMaker to automate and scale the ML lifecycle. What is FMEval?

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Large Language Models Algorithm LLM Responsible AI 109

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 112

Data Scientist ML Data Science Machine Learning 112

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. We asked ourselves, what if we leverage the zero-shot capability of LLMs, or large foundation models and our own proprietary algorithms fine-tuning auto labeling layer?

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Automation Auto-complete Computer Vision ChatGPT 98

Pickl AI

APRIL 5, 2023

This makes it easier for you to understand the algorithm and the different techniques used in Machine Learning. Moreover, you will also learn the use of clustering and dimensionality reduction algorithms. This course is useful for Data Scientists who are keen to expand their expertise in ML.

Machine Learning 52

Machine Learning ML Engineer ML Data Scientist 52

AssemblyAI

DECEMBER 15, 2022

To use Photostudio, a user clicks a picture using their phone and then multiple AI Image algorithms are used to generate stunning product images while preserving all details of the original product. Shubham Saboo (Head of DevRel at Tenstorrent Inc.

Software Engineer 130

Software Engineer ML Engineer Data Scientist AI Chatbots 130

Towards AI

FEBRUARY 11, 2025

🚀 MLflow Experiment Tracking: The Ultimate Beginners Guide to Streamlining ML Workflows Photo by Alvaro Reyes on Unsplash Introduction Have you ever felt that you were losing command over your machine-learning projects? The algorithm in question? Sound familiar? If you facing this problem, then you are not alone.

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ML Machine Learning Data Scientist ML Engineer 67

AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers to explain the predictions of their ML models.

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Explainability Algorithm Natural Language Processing Machine Learning 85

Unite.AI

SEPTEMBER 3, 2024

While GPUs were initially designed for rendering graphics, their architecture makes them exceptionally well-suited for the parallel processing requirements of many machine learning algorithms. Matrix Multiplication Matrix multiplication is a fundamental operation in many machine learning algorithms, particularly in neural networks.

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Machine Learning Convolutional Neural Networks Neural Network Algorithm 130

Flipboard

SEPTEMBER 4, 2023

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. Switching gears, imagine yourself being part of a high-tech research lab working with Machine Learning algorithms.

Machine Learning 150

Machine Learning Computer Vision Deep Learning Python 150

AWS Machine Learning Blog

JANUARY 13, 2023

Machine learning (ML) presents an opportunity to address some of these concerns and is being adopted to advance data analytics and derive meaningful insights from diverse HCLS data for use cases like care delivery, clinical decision support, precision medicine, triage and diagnosis, and chronic care management. He received his Ph.D.

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Machine Learning ML Algorithm Data Scientist 91

AWS Machine Learning Blog

JANUARY 5, 2024

The customer used this pipeline for small and medium scale models, which included using various types of open-source algorithms. One of the key benefits of SageMaker is that various types of algorithms can be brought into SageMaker and deployed using a bring your own container (BYOC) technique.

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Data Science Data Drift DevOps Auto-complete 131