Unite.AI

JUNE 19, 2024

Master's Degree : Pursuing a Master's degree in Computer Science, Data Science, or a related field can further enhance your knowledge and skills, particularly in areas like ML, AI, and advanced software engineering concepts. Krish Naik : Focuses on machine learning, data science, and MLOps.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

ODSC - Open Data Science

FEBRUARY 9, 2023

It is often too much to ask for the data scientist to become a domain expert. However, in all cases the data scientist must develop strong domain empathy to help define and solve the right problems. Nina Zumel and John Mount, Practical Data Science with R, 2nd Ed.

Data Scientist 105

Data Scientist Machine Learning ML Engineer ML 105

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

ML 152

ML DevOps Data Scientist ML Engineer 152

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, 2021. [6]

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

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.

Machine Learning 98

Machine Learning ML Engineer ML Data Science 98

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. Prior experience in Python, ML basics, data training, and deep learning will come in handy for a smooth ride ahead.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

ODSC - Open Data Science

MARCH 27, 2023

ML Governance: A Lean Approach Ryan Dawson | Principal Data Engineer | Thoughtworks Meissane Chami | Senior ML Engineer | Thoughtworks During this session, you’ll discuss the day-to-day realities of ML Governance. Some of the questions you’ll explore include How much documentation is appropriate?

Machine Learning 98

Machine Learning Data Science Deep Learning Data Ingestion 98

The MLOps Blog

JUNE 27, 2023

With built-in components and integration with Google Cloud services, Vertex AI simplifies the end-to-end machine learning process, making it easier for data science teams to build and deploy models at scale. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

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 111

Data Scientist ML Data Science Automation 111

AWS Machine Learning Blog

APRIL 29, 2024

Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. He is also the author of a book, Effective Data Science Infrastructure, published by Manning.

ML 120

ML Python Data Scientist Deep Learning 120

Towards AI

AUGUST 24, 2023

Since this is an AI website, I will assume that most readers will have the following goals: You are interested in becoming an AI/ML engineer. You are interested in learning software engineering best practices [1][2]. Thus, deep learning models should be your last choice. Know when not to use AI.

Neural Network 98

Neural Network Software Engineer Algorithm Machine Learning 98

O'Reilly Media

OCTOBER 19, 2021

This introduces further requirements: The scale of operations is often two orders of magnitude larger than in the earlier data-centric environments. Not only is data larger, but models—deep learning models in particular—are much larger than before. Adapted from the book Effective Data Science Infrastructure.

DevOps 145

DevOps Software Engineer Data Scientist ML 145

Heartbeat

FEBRUARY 1, 2023

Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. In this article, we’ll learn everything there is to know about these operations and how ML engineers go about performing them. What is MLOps? We pay our contributors, and we don’t sell ads.

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96

AWS Machine Learning Blog

SEPTEMBER 20, 2023

SageMaker Studio allows data scientists, ML engineers, and data engineers to prepare data, build, train, and deploy ML models on one web interface. The code snippets in the following sections have been tested in the SageMaker Studio notebook environment using the Data Science 3.0

ML 122

ML Python Deep Learning Machine Learning 122

Pickl AI

NOVEMBER 28, 2024

Continuous learning is essential to keep pace with advancements in Machine Learning technologies. Fundamental Programming Skills Strong programming skills are essential for success in ML. Python’s readability and extensive community support and resources make it an ideal choice for ML engineers.

Machine Learning 52

Machine Learning Neural Network ML Engineer Algorithm 52

ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These data owners are focused on providing access to their data to multiple business units or teams. Data science team – Data scientists need to focus on creating the best model based on predefined key performance indicators (KPIs) working in notebooks.

Generative AI 123

Generative AI Prompt Engineering Prompt Engineer ML 123

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

Heartbeat

OCTOBER 23, 2023

Revolutionizing Healthcare through Data Science and Machine Learning Image by Cai Fang on Unsplash Introduction In the digital transformation era, healthcare is experiencing a paradigm shift driven by integrating data science, machine learning, and information technology.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

Heartbeat

SEPTEMBER 6, 2023

There are machine learning platforms that can perform all these tasks, and Comet is one such platform. Comet Comet is a machine learning platform built to help data scientists and ML engineers track, compare, and optimize machine learning experiments. Thanks for reading!

Machine Learning 52

Machine Learning Deep Learning Auto-complete Data Scientist 52

ODSC - Open Data Science

JANUARY 10, 2024

Learn more about our first-announced sessions coming to the event this April 23rd-25th below. Causal AI: from Data to Action Dr. Andre Franca | CTO | connectedFlow Explore the world of Causal AI for data science practitioners, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions.

Large Language Models 52

Large Language Models Deep Learning LLM Data Science 52

ODSC - Open Data Science

FEBRUARY 22, 2024

By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows. Using Graphs for Large Feature Engineering Pipelines Wes Madrigal | ML Engineer | Mad Consulting Feature engineering from raw entity-level data is complex, but there are ways to reduce that complexity.

Machine Learning 52

Machine Learning Data Science Python ML 52

Pickl AI

MAY 30, 2023

For instance, Data Science Course with Placement Guarantee is one of the most in-demand courses that aspirants are looking for. Instances of Professionals courses include Data Science Bootcamp Job Guarantee, Python for Data Science, Data Analytics, Business Analytics, etc. Lakhs annually.

Data Mining 52

Data Mining Data Science Machine Learning Deep Learning 52

Mlearning.ai

FEBRUARY 9, 2023

11 key differences in 2023 Photo by Jan Tinneberg on Unsplash Working in Data Science and Machine Learning (ML) professions can be a lot different from the expectation of it. In the industry, deep learning is not always the preferred approach. This is even more common for first-time baseline models.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 18, 2023

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. Mark Hallows is a Remote Sensing Specialist at Arup, based in London.

Data Scientist 116

Data Scientist ML Machine Learning ML Engineer 116

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.

Generative AI 128

Generative AI Prompt Engineering Prompt Engineer LLM 128

AWS Machine Learning Blog

APRIL 25, 2023

This allows ML engineers and admins to configure these environment variables so data scientists can focus on ML model building and iterate faster. You can select the Data Science 3.0 SageMaker uses training jobs to launch this function as a managed job. SchemaVersion: '1.0'

Machine Learning 94

Machine Learning Data Scientist Python ML 94

Dlabs.ai

OCTOBER 21, 2024

#InsideAI Frequency: Monthly Best for: Business leaders, AI professionals, entrepreneurs, and those interested in practical AI applications Content: Comprehensive coverage of AI, machine learning, and data science developments This newsletter provided by DLabs.AI delivers the most important news to you every month.

Deep Learning 52

Deep Learning AI AI Machine Learning 52

AWS Machine Learning Blog

MARCH 1, 2023

These are all implemented as a single ML pipeline using Amazon SageMaker Pipelines , and all the ML trainings are managed via Amazon SageMaker Experiments. ML engineers no longer need to manage this training metadata separately. ML model We selected AutoGluon for model training implemented with SageMaker pipelines.

Automation 99

Automation ETL Data Drift ML 99

DataRobot Blog

SEPTEMBER 13, 2022

Once an organization has identified its AI use cases , data scientists informally explore methodologies and solutions relevant to the business’s needs in the hunt for proofs of concept. These might include—but are not limited to—deep learning, image recognition and natural language processing.

Data Scientist 52

Data Scientist Automation ML Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Throughout this exercise, you use Amazon Q Developer in SageMaker Studio for various stages of the development lifecycle and experience firsthand how this natural language assistant can help even the most experienced data scientists or ML engineers streamline the development process and accelerate time-to-value.

ML 82

ML Computer Vision Data Scientist Machine Learning 82

Heartbeat

OCTOBER 5, 2023

Illustration from the book —  Effective Data Science Infrastructure The Future of LLMOps As we look ahead, LLMOps promises exciting advancements in various areas: Privacy-Preserving and Federated Learning: LLMOps will focus on preserving privacy while training models on decentralized data.

Large Language Models 52

Large Language Models DevOps Machine Learning Prompt Engineering 52

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

AWS Machine Learning Blog

OCTOBER 2, 2024

About the Authors Akarsha Sehwag is a Data Scientist and ML Engineer in AWS Professional Services with over 5 years of experience building ML based services and products. Leveraging her expertise in Computer Vision and Deep Learning, she empowers customers to harness the power of the ML in AWS cloud efficiently.

Generative AI 118

Generative AI Data Ingestion AI AI 118

AWS Machine Learning Blog

AUGUST 16, 2023

The original concept came out of an AI/ML Hackathon supported by Simone Zucchet (AWS Solutions Architect) and Tim Precious (AWS Account Manager) and was developed into production using AWS services in under 6 weeks with support from AWS. Prior to this role, he was the Head of Data Science for Amazon’s EU Customer Service.

Large Language Models 90

Large Language Models Machine Learning Generative AI ML 90

Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Heartbeat

JULY 17, 2023

Comet allows ML engineers to track these metrics in real-time and visualize their performance using interactive dashboards. Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners.

Computer Vision 52

Computer Vision Auto-classification Deep Learning Machine Learning 52